2.097 Ofertas de Redes Neuronales en Argentina

BDO Argentina continúa expandiéndose y tenemos una propuesta para vos.

¡Abrimos 1 nueva vacante para el área de GRC!

¿Qué buscamos?

• Perfiles con al menos 5 años de experiencia como Analista Senior en Ciencia de Datos, con sólida formación en machine learning, procesamiento de datos y despliegue de soluciones en entornos productivos.

Tareas Habituales

• Diseñar y conceptualizar modelos predictivos y representativos, aplicando criterios estadísticos avanzados (análisis multivariado, validación de patrones, detección de anomalías).
• Manipular, explorar, limpiar y preparar fuentes de datos diversas (estructuradas, no estructuradas, geoespaciales) para su procesamiento y análisis.
• Desarrollar e implementar técnicas de machine learning supervisado y no supervisado (boosting, clustering, autoencoders, NLP, embeddings, transformers).
• Orquestar pipelines de datos y procesamiento distribuido (Spark, Dask), asegurando la calidad y trazabilidad de los experimentos (MLflow, Airflow).
• Desplegar modelos y microservicios en producción (FastAPI, Flask, Docker, Kubernetes), integrando APIs y sistemas de autenticación y permisos.
• Desarrollo de agentes inteligentes para automatización de procesos, atención al cliente, auditoría y gestión documental.
• Implementación de arquitecturas RAG (Retrieval-Augmented Generation) para agentes que integran modelos generativos con acceso a fuentes de datos internas y externas.
• Diseño de prompts avanzados, gestión de contexto y orquestación de flujos de información multimodal.
• Integración de sistemas de recomendación, scoring y segmentación en agentes conversacionales y asistentes virtuales.

Formá parte de un equipo de trabajo de alto rendimiento. Participación directa en variedad de industrias y clientes. Buenas condiciones de contratación. Buen clima laboral.

Sumate a BDO!

Formamos talentos. Potenciamos líderes.

Requisitos

• Experiencia en proyectos de automatización, chatbots, sistemas de recomendación, scoring, segmentación y clustering.
• Dominio de frameworks y herramientas como PyTorch, TensorFlow, Scikit-Learn, XGBoost, LightGBM, spaCy, Transformers.
• Conocimientos en MLOps, despliegue en la nube (Azure).
• Certificaciones relevantes en machine learning, MLOps, análisis de datos y BI.

Beneficios

• Medicina prepaga Swiss Medical para todo tu grupo familiar.
• Esquema híbrido de trabajo o 100% remoto si residis en el interior del país.
• Vacaciones flex - días hábiles + días adicionales por antigüedad.
• Formación técnica continua, aprende con nuestros especialistas.
• Programa de Formación de lideres. Te acompañamos en el desafío de liderar equipos.
• Capacitación en Ingles.
• Wellhub. Accede a gimnasios, estudios y clases para tu bienestar.
• Descuentos en carreras de grado y postgrado en universidades de primer nivel.
• Día de cumpleaños libre.
• Día libre para padres/madres, en vacaciones de invierno.
• Día de mudanza.
• Soft Landing Maternidad.
• Licencia de paternidad extendida.
• Descuentos en +2000 comercios adheridos, centros de estudios, clases de yoga, wellness, shows y muchas cosas más!

Las oportunidades laborales para trabajar en BDO en Argentina, son solo aquellas publicadas en la plataforma Hiring Room de la empresa.

En BDO ofrecemos mucho más que servicios de Auditoría, Consultoría, Impuestos, Outsourcing & Payroll somos personas ayudando a personas a alcanzar sus sueños, combinando calidad y estándares internacionales con la calidez y los valores que nos caracterizan.

#TrabajemosJuntos. Buscamos un/a Analista estrategico de salud con conocimiento en ciencia de datos

Quien ingrese tendrá el desafio de d iseñar, prototipar e implementar soluciones basadas data science aplicadas al negocio, colaborando con áreas analíticas y estratégicas para optimizar procesos y desarrollar capacidades predictivas. Generar información para la toma de decisiones y realizar seguimiento de las variables principales del negocio

Tus principales responsabilidades serán:

• Proyectar niveles de consumo y anticipar desvíos. Clasificaciones de asociados por características de consumo.
• Desarrollar tableros de control sobre variables del negocio.
• Generar análisis sobre problemáticas de negocio.
• Automatizar información utilizada en la toma de decisiones y en procesos operativos.

Nos orientamos a profesionales con solido conocimiento en ciencia de datos, armado de informe y propuesta de mejoras. Con motivación por trabajar en equipo. #estoydondequieroestar

• Profesional en Ciencia de Datos, Ing. Sistemas/Industrial, Estadistica, Matematicas, Economia afines(Excluyente)
• Experiencia práctica con los siguientes enfoques: Modelos predictivos clásicos, NPL aplicado a textos médicos o administrativos, Automatización con APIs o scripts. (Excluyente)
• Excel Avanzado (Tablas dinámicas/ Power Query /Power Pivot)
• Conocimiento en herramientas de visualización de datos.
• Conocimiento en herramientas de visualización de datos.

• Ser parte de uno de los principales Grupos de Medicina Privada y Grupo Empresario a escala nacional que, a través de sus diferentes unidades de negocio, brinda soluciones y desarrolla productos enfocados en proteger el bienestar de los argentinos.

• Ser protagonista de tu desarrollo profesional. ¡A través de nuestra propia Universidad Corporativa acompañamos tu formación!

• Trabajar con pasión, compromiso, cercanía e innovación sin perder de vista nuestros orígenes, para ofrecer servicios de excelencia.

En SanCor Salud #EstoyDondeQuieroEstar

Nivel mínimo de educación: Universitario (Graduado)

Somos Grupo SanCor Salud , uno de los principales Grupos de Medicina Privada y Grupo Empresario. A través de nuestras diferentes unidades de negocio, brindamos soluciones y desarrollamos productos enfocados en preservar el bienestar de los argentinos. Trabajamos con energía y entusiasmo para ofrecer calidad de servicio a personas y empresas, sin perder de vista nuestros orígenes y valores.

En SanCor Salud tenemos una oportunidad para quienes:

• Incentiven la cercanía y el buen clima laboral.

• Desafíen los procesos y abran camino a formas innovadoras de trabajo.

• Se desempeñen con pasión , profesionalismo y compromiso .

• Disfruten trabajar en equipos colaborativos y multidisciplinarios

¡Sumate vos también y #DesafiateConNosotros !

#TrabajemosJuntos. Buscamos un/a Analista estrategico de salud con conocimiento en ciencia de datos

Quien ingrese tendrá el desafio de d iseñar, prototipar e implementar soluciones basadas data science aplicadas al negocio, colaborando con áreas analíticas y estratégicas para optimizar procesos y desarrollar capacidades predictivas. Generar información para la toma de decisiones y realizar seguimiento de las variables principales del negocio

Tus principales responsabilidades serán:

• Proyectar niveles de consumo y anticipar desvíos. Clasificaciones de asociados por características de consumo.
• Desarrollar tableros de control sobre variables del negocio.
• Generar análisis sobre problemáticas de negocio.
• Automatizar información utilizada en la toma de decisiones y en procesos operativos.

Nos orientamos a profesionales con solido conocimiento en ciencia de datos, armado de informe y propuesta de mejoras. Con motivación por trabajar en equipo.

#estoydondequieroestar

• Profesional en Ciencia de Datos, Ing. Sistemas/Industrial, Estadistica, Matematicas, Economia afines(Excluyente)
• Experiencia práctica con los siguientes enfoques: Modelos predictivos clásicos, NPL aplicado a textos médicos o administrativos, Automatización con APIs o scripts. (Excluyente)
• Excel Avanzado (Tablas dinámicas/ Power Query /Power Pivot)
• Conocimiento en herramientas de visualización de datos.
• Conocimiento en herramientas de visualización de datos.

• Ser parte de uno de los principales Grupos de Medicina Privada y Grupo Empresario a escala nacional que, a través de sus diferentes unidades de negocio, brinda soluciones y desarrolla productos enfocados en proteger el bienestar de los argentinos.

• Ser protagonista de tu desarrollo profesional. ¡A través de nuestra propia Universidad Corporativa acompañamos tu formación!

• Trabajar con pasión, compromiso, cercanía e innovación sin perder de vista nuestros orígenes, para ofrecer servicios de excelencia.

En SanCor Salud #EstoyDondeQuieroEstar

Nivel mínimo de educación: Universitario (Graduado)

Somos Grupo SanCor Salud , uno de los principales Grupos de Medicina Privada y Grupo Empresario. A través de nuestras diferentes unidades de negocio, brindamos soluciones y desarrollamos productos enfocados en preservar el bienestar de los argentinos. Trabajamos con energía y entusiasmo para ofrecer calidad de servicio a personas y empresas, sin perder de vista nuestros orígenes y valores.

En SanCor Salud tenemos una oportunidad para quienes:

• Incentiven la cercanía y el buen clima laboral.

• Desafíen los procesos y abran camino a formas innovadoras de trabajo.

• Se desempeñen con pasión , profesionalismo y compromiso .

• Disfruten trabajar en equipos colaborativos y multidisciplinarios

¡Sumate vos también y #DesafiateConNosotros !

Job Title: Senior Full-stack Engineer

Work Arrangement: Remote| Must be able to work EST hours

Job Type: Full-time

Salary: Competitive base salary in USD

Industry: PropTech / B2B SaaS / Real Estate Technology

Work Schedule: 40 hours per week

Pearl works with the top 1% of candidates from around the world and connects them with the best startups in the US and EU. Our clients have raised over $5B in aggregate and are backed by companies like OpenAI, a16z, and Founders Fund. They're looking for the sharpest, hungriest candidates who they can consistently promote and work with over many years. Candidates we've hired have been flown out to the US and EU to work with their clients, and even promoted to roles that match folks onshore in the US.

Hear why we exist, what we believe in, and who we're building for: Watch here

We're not just another recruiting firm—we focus on placing candidates with exceptional US and EU founders who prioritize the long-term success of their team members. We also provide retention bonuses at 3, 6, 9, and 12 months, as well as community-driven benefits like an annual retreat.

Our partner company helps the world's most prominent companies navigate their most important brand, reputation, and product challenges. We specialize in high-impact research with hard-to-reach audiences -- recruiting the exact audiences our clients need, anywhere in the world. Our in-house teams ensure rigorous quality, rapid execution, and clear, strategic insights. Every engagement is custom-built, senior-led, and designed to deliver answers that drive key decisions.

Key Responsibilities

·      Train and evaluate ML models using common machine learning frameworks in Python. Examples include TensorFlow, Keras, scikit-learn, or PyTorch.

·      Develop and refine NLP pipelines (e.g., tokenization, entity recognition, similarity models).

·      Perform fine-tuning and prompt engineering for LLMs (GPT, Claude, etc.).

·      Create semantic search and recommendation models using vector embeddings and clustering techniques.

·      Conduct experiments, hyperparameter tuning, and performance benchmarking.

·      Collaborate with software engineers to integrate models into backend systems.

·      Prepare clear documentation, model cards, and evaluation reports.

Required Skills

·      Strong proficiency in Python for machine learning and data processing.

·      Experience with NLP libraries: spaCy, Hugging Face Transformers, gensim, nltk.

·      Comfortable training deep learning models using Keras, TensorFlow, or PyTorch.

·      Ability to design and execute ML experiments, evaluate models, and interpret results.

·      Familiar with version control (Git), shell scripting, and Linux development environments.

·      Basic back end software engineering skills, such as creating and managing endpoints, database services, and task queues.

· Experience with production environments (e.g., batch inference, model packaging).

Nice to Have

·      Experience with MLOps tools (e.g., MLflow, SageMaker, DVC).

·      Contributions to Kaggle competitions, AI research, or open-source ML/NLP projects.

·      Background in classical ML, unsupervised learning, or semantic modeling.

Working Conditions

·      Fully remote, must be able to collaborate during EST hours.

·      Work closely with backend/frontend engineers, but not expected to build application UIs.

·      Focused environment for pure AI/ML development, research, and delivery.

Why Join Now

• Be a foundational member of a venture-scale company with real distribution advantages in real estate.
• Own key technical systems from day one, shaping how they evolve.
• Culture built on speed, iteration, and execution.

• Professional Development: Annual learning budget for books, courses, and conferences
• Mentorship: Learn directly from startup veterans (ex-Looker, GitHub, Mulesoft)
• Impact: Help shape a growing brand with a voice that influences fintech innovation
• Inspiring Workspaces: Offices in Berlin, New York, and London, with travel opportunities
• Flat Hierarchy: Work directly with founders and have your ideas heard
• Flexible Work Setup: Equipment of your choice, strong home office support

1. Application
2. Screening
3. Top-grading Interview
4. Skills Assessment
5. Client Interview
6. Offer
7. Onboarding

Buscamos un Machine Learning / AI Engineer Senior con un sólido enfoque en MLOps y Python que también pueda desempeñarse como AI Engineer para soluciones de IA generativa. Será responsable registrar experimentos, métricas y modelos, construir pipelines reproducibles para entrenamiento, validación o inferencia asi tambien como mantener versiones de datos, artefactos y modelos, garantizando trazabilidad y colaboración.

Conocimientos requeridos

Lenguaje y frameworks de ML & Generative AI

• Python 3.xx (tipos, Pydantic, AsyncIO) con ecosistema científico (Pandas, NumPy,Polars).
  Frameworks de deep learning: PyTorch- 2.x, TensorFlow 2.x/Keras, JAX/Flax.
• Frameworks de agentes y orquestación GenAI: LangChain, LangGraph,LlamaIndex, CrewAI, AutoGen.
  
  Plataforma MLOps & Experimentación
• Tracking y registro de modelos: MLflow Tracking + Model Registry
• Orquestación de pipelines: Kubeflow Pipelines, Argo Workflows, AWS, SageMaker Pipelines, Vertex AI Pipelines.
• Versionado de datos/artefactos: DVC, LakeFS.
  
  Observabilidad y monitoreo
• Métricas y trazabilidad: Prometheus, Grafana, OpenTelemetry.
• Calidad de datos/modelos: Evidently AI, WhyLabs.
  
  Vector DB, RAG & búsqueda semántica
• Bases vectoriales: Pinecone, Weaviate, Milvus, pgvector.
• Toolkits RAG: LangChain Retrievers, LlamaIndex integrations.
  
  Entorno Cloud & Serverless GenAI
• Servicios managed GenAI: AWS Bedrock, Azure OpenAI Service, Google Gemini, Anthropic Claude.
• Serverless/event‐driven: AWS Lambda, Google Cloud Functions, Cloud Run,Requisitos del perfil
  +5 años de experiencia en ML/AI engineering, con- 2 años dedicados a MLOps en producción.
• Experiencia desplegando sistemas RAG a escala.
• Capacidad para liderar iniciativas técnicas y coordinar equipos multidisciplinarios.
• Residencia en Buenos Aires, Argentina o disponibilidad para esquema híbrido.
• Valorable experiencia en sector financiero o consultoría tecnológica B2B.

Responsabilidades clave

• Diseñar y mantener pipelines de ML y LLMs (entrenamiento, fine‐tuning, inferencia,
  
  retraining).
• Desplegar modelos ML en producción.
• Implementar y gobernar vector stores y pipelines RAG para exponer capacidades
  
  de IA generativa sobre datos corporativos.
• Colaborar en la operacion del equipo (estimaciones técnicas, demos y RFPs).
• Liderar revisiones de arquitectura con foco en escalabilidad, resiliencia y
  
  compliance.
• Investigar continuamente la evolución de la IA generativa para proponer
  
  innovaciones.

We're looking for a Machine Learning Engineer who loves building real products and shipping code. If you enjoy owning production systems, solving tough engineering problems, and bringing cool ML research into real-world applications, you'll love it here

Identity security today sucks. People hate passwords, 2FA codes, and security questions; it's an endless cycle of frustration. At TWOSENSE.AI, we're fixing this using AI-powered behavioral biometrics. The system we created automatically recognizes people by their unique behaviors—how you type, move the mouse, or even walk—creating the world's first invisible, private biometric. No passwords, no puzzles—just seamless security that's always on. Our mission is to fundamentally change secure human-computer interactions, making forgotten passwords and frustrating authentication a thing of the past.

We're an engineer-founded and led team of PhDs and exceptional software engineers based in Brooklyn, NYC. Transparency, autonomy, continuous improvement, and strong engineering culture matter deeply to us. Right now, we're fully remote and plan to stay flexible for the foreseeable future. As an early team member, you'll directly shape our strategy, trajectory, and your own career as you grow with us.

• Build and maintain our production ML pipeline—including ETL processes, data cleaning, preprocessing, feature extraction, training, evaluation, deployment, and monitoring.
• Develop streamlined ML workflows to effectively support our production systems.
• Write clean, maintainable Python code using test-driven or test-first development practices.
• Collaborate closely with founders and researchers to bring ML ideas to life—with opportunities to participate directly in research projects.
• Optimize our infrastructure to handle growth and scale effectively.

• Strong software engineering skills—grounded in SOLID principles and best practices.
• Hands-on experience deploying ML models to production.
• Experience with common ML libraries like scikit-learn, TensorFlow, or PyTorch.
• Basic understanding of ML fundamentals (algorithms, math/stats), along with strong intuition for how and when to apply different modeling approaches.

• Familiarity with developing and deploying ML systems using AWS tools and infrastructure.
• Experience with varied data types (structured, time-series).
• Previous experience with behavioral biometrics or security-focused products.
• Previous experience with ONNX.

Salary ranges:

• Argentina - $70,000 - $90,000

We genuinely care about our people. Here's how:

• Flexible working—remote or in-office, whatever suits you best.
• Project Day once a month—dedicate a day to something you're passionate about.
• Equity—share directly in our success.
• Open vacation policy—take time off whenever you need.
• Subscription to online learning resources like O'Reilly and Pluralsight.

Extra perks for our Argentina-based folks:

• Business English courses.
• Travel for team events and company meet-ups.
• Technical books, VPN, and high-end work equipment provided.

We're growing fast, and you'll have plenty of opportunities to shape the company, influence our direction, and rapidly grow your career.

We are actively seeking a highly skilled ML/AI/NLP Developer to join our team and lead the development of consumer-oriented features. If you're passionate about artificial intelligence, innovation, and using data-driven solutions to solve real product challenges, this is your opportunity to make an impact.

We're looking for someone with strong technical and analytical abilities, capable of independently conducting research and delivering smart, efficient solutions. In this role, you'll collaborate with stakeholders to understand product needs and goals, and then leverage your expertise in ML/AI/NLP to build and implement improvements that truly make a difference.

Once opportunities for enhancement are identified, you will autonomously develop and implement solutions, working closely with developers and product managers to deploy these features to end-users. You will also be responsible for continuously monitoring and optimizing the performance of these features based on user feedback and data insights.

We're looking for a proactive team player ready to take the lead on our ML/AI/NLP initiatives and committed to staying current with the latest advancements in the field.

Responsibilities:

• As a ML/AI/NLP Developer, you will play a pivotal role in integrating intelligent technologies into our products to improve the user experience and increase customer retention. Your key responsibilities include:
• Taking the lead in advancing our ML/AI/NLP initiatives by identifying and analyzing areas of opportunity within the current product.
• Conducting continuous research on existing ML/AI/NLP technologies and trends, identifying innovative tools and practices we can adopt.
• Designing and proposing creative ML/AI/NLP-based solutions that elevate the customer journey and product experience.
• Collaborating with cross-functional teams—developers, designers, content managers, and product managers—to implement, monitor, optimize, and deploy AI-driven solutions.
• Evaluating and integrating third-party ML/AI/NLP tools and services to expand our internal capabilities.

Requirements:

• 3+ years of hands-on experience developing and deploying ML/AI/NLP models in real-world applications.
• Proven ability to independently identify product improvement opportunities through ML/AI/NLP technologies, conduct relevant research, and implement tangible solutions

About Trafilea

Trafilea is a dynamic and innovative Tech E-commerce Group that operates multiple direct-to-consumer brands in the intimate apparel and beauty sectors, with a focus on using data-driven strategies to scale their businesses. In addition to our products, we have our own online community dedicated to promoting body positivity. As a rapidly growing global player, Trafilea is committed to creating high-quality products and services that enhance the customer experience and drive long-term growth.

At Trafilea, we foster a culture of collaboration, innovation, and continuous learning. We believe in investing in our people and providing them with the support and development opportunities they need to grow both personally and professionally. With our remote-first approach, you'll have the freedom to work from anywhere in the world, surrounded by a diverse and talented team that spans the globe.

Mission

As a
Senior Machine Learning Engineer
, you'll lead the development and deployment of advanced models, driving innovation and efficiency across the organization. This role involves crafting production-ready code, designing systems within the overarching architecture, and applying scientific methodologies to solve complex problems. Bridging the gap between business strategy and technical execution, you will ensure that machine learning projects align with company goals, delivering tangible value.

With your expertise, we'll harness the power of machine learning to unlock opportunities, streamline processes, and maintain our position at the forefront of technological advancement.

General Accountabilities

• Develop and maintain production-ready machine learning code that is testable, well-documented, and accounts for edge cases and errors.
• Design code that aligns with the service architecture, utilizing effective abstractions and code isolation.
• Write comprehensive tests covering edge cases, errors, and happy paths following the testing pyramid.
• Gain a high-level understanding of the team's domain and develop expertise in a specific portion of it, contributing significantly to the team's projects.
• Apply the scientific method to bring insights from research directly into all areas of the team's project, showcasing innovative ideas, technologies, or techniques.
• Master the application of theory to practice, iterating through the KDD process, understanding the Deep Learning ecosystem, focusing on robust and scalable ML processes, and developing efficient data pipelines.
• Integrate business and technical strategies, contributing to business discussions and aligning technical projects with business goals.
• Ensure tasks are critically reviewed, appropriately sized, and prioritized, and dependencies are managed for continuous integration and incremental delivery.
• Deliver and encourage the delivery of constructive feedback within the team and to business stakeholders, fostering a culture of continuous improvement.
• Communicate effectively in both technical and non-technical terms, ensuring clarity and audience engagement, while actively listening and paying attention to nonverbal cues.
• Share knowledge frequently, contribute to team documentation, and encourage a culture of knowledge sharing and mentorship within the team.

Role-related Competencies & Requirements

• Graduated in Computer Science, Mathematics, Statistics, or a related field with a strong focus on machine learning, or advanced student (min 3rd degree completed)
• Minimum of 5 years of experience in machine learning engineering, with a proven track record of developing and deploying robust, scalable machine learning models.
• Expertise in writing production-ready code, with a strong understanding of the testing pyramid and experience in writing comprehensive tests.
• Deep knowledge of the machine learning development lifecycle, including the KDD process, Deep Learning ecosystems, MLOps practices, and data engineering.
• Ability to integrate business strategy with technical execution, contributing to business discussions and ensuring alignment of machine learning projects with business objectives.
• Strong communication skills, capable of conveying complex technical concepts in simple terms to a diverse audience, and fostering a culture of open, effective communication within the team.
• Leadership in fostering a culture of continuous improvement, knowledge sharing, and mentorship within the team.
• Proficiency in advanced ML tools and programming languages used in data science (e.g., Python, R, SQL).
• Proficiency in ML cloud services and Saas tools like MLFlow and AWS ecosystem.
• Proven experience in marketing, e-commerce marketplace, or growth teams.

Expected Outcomes for initial 3 months

First 30 Days:

Understand the current machine learning landscape, including tools, frameworks, and ongoing projects within the company. Establish relationships with key stakeholders and identify immediate areas for impact.

First 60 Days:

Develop and deploy at least one major machine learning model or improvement, demonstrating expertise in code quality, testing, and alignment with business goals. Begin mentoring team members and contributing to knowledge sharing.

First 90 Days:

Lead a significant machine learning project from concept to deployment, showcasing the ability to integrate technical and business strategies. Implement and advocate for improvements in team practices and processes, enhancing overall efficiency and collaboration.

What we offer

• Collaborate with world-class talents in a data-driven, dynamic, energetic work environment.
• Opportunity to grow and develop both professionally and personally.
• Safe space to be who you truly are, with a commitment to diversity, equity, and inclusion.
• Openness to new ideas and initiatives.
• Great benefits package including remote work, 15 working days of paid holidays, Learning subsidy, and more

Who We Are
SQUIRE is the leading business management system designed for the needs of barbers, shop owners, and their communities.

We believe the pursuit of artistry and autonomy should not be restricted by the complexities of running a business.

With SQUIRE, we provide custom-branded tools, resources, and guidance to help barbers of all stages and experience levels attract and retain more customers, efficiently manage their shop operations, and increase their revenue.

Founded in 2015, SQUIRE is trusted by barbers in 4,000+ shops in more than a thousand cities around the globe.

From streamlined booking and opening new shops to real-time earning dashboards and building lasting customer relationships, SQUIRE supports shop owners in seamlessly bridging the gap between their personal craft and business goals.

SQUIRE enables barbers everywhere to unlock their full potential both as artists and as entrepreneurs.

For more information, please visit

or download the SQUIRE app from the App or Play Store.

We're hiring a Machine Learning Engineer to embed into our product teams and own the entire ML lifecycle—from prototype to production.

This is not a role for model research or experimentation in a vacuum.

We're looking for an engineer who thrives on taking state-of-the-art ML (especially LLMs and AWS-based solutions) and transforming it into deployed, maintainable, and scalable real-world systems that power SQUIRE's products.

If you're passionate about building practical ML applications and turning ideas into shipping features, this role is for you.

Job Duties & Responsibilities
Own the full ML lifecycle for product features—from ideation to deployment, observability, and iteration

Use off-the-shelf models (e.g. in AWS SageMaker, Bedrock, Comprehend, HuggingFace) to solve core user and business problems

Build and maintain robust, scalable ML pipelines and infrastructure (batch and real-time)

Work cross-functionally with product managers, designers, and backend engineers to ship ML-powered features

Drive productionization: model inference, latency tuning, monitoring, logging, and failure recovery

Continuously evaluate and integrate emerging models (especially LLMs) to improve accuracy and capabilities

Bring an engineering mindset to ML work—automate processes, reduce tech debt, and champion good software practices in the ML stack

The duties and responsibilities outlined above are not a comprehensive list, and additional tasks may be assigned based on business needs.

Ideal Requirements & Qualifications
3+ years of experience in machine learning engineering, ideally within a product-oriented tech team

Strong software engineering background with experience writing clean, scalable, and maintainable code in Python

Hands-on experience using cloud-based ML services (especially AWS) and pre-trained models in production

Experience with modern deployment stacks and MLOps: CI/CD, model versioning, monitoring, etc

A pragmatic mindset—you value impact, simplicity, and reliability over academic perfection

NICE TO HAVE

Experience integrating LLMs into products via APIs or fine-tuning

Familiarity with React Native applications or full-stack development environments

Prior work in consumer or SMB-facing products.

WHY JOIN SQUIRE?

Work on impactful, customer-facing features powered by machine learning

Help shape our AI-first engineering culture

Enjoy autonomy and ownership over your domain with the support of an exceptional engineering team

Competitive salary, equity, and benefits in a high-growth, mission-driven company

Interview Accommodations

SQUIRE is committed to working with and providing reasonable assistance to individuals with physical and mental disabilities.

If you are an individual with a disability requiring an accommodation to apply for an open position, please email your request to *** and someone on our team will respond to your request.

Equal Employment Opportunity

SQUIRE provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Pay Transparency Nondiscrimination Provision

SQUIRE will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant.

However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is

• in response to a formal complaint or charge,
• in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or
• consistent with the contractor's legal duty to furnish information.