Senior Machine Learning Engineer

We are looking for a
Senior Machine Learning Engineer
with strong
backend engineering expertise
to help build and scale our personalization and recommendations system. In this role, you'll design and deploy intelligent, personalized recommendations that drive real user engagement, while also contributing to the underlying backend services and infrastructure that power these systems. This is a hands-on, cross-functional role ideal for someone who thrives at the intersection of machine learning, backend systems, and product impact.

Responsibilities

• Design, implement and maintain scalable ML infrastructure and production systems
• Closely collaborate with Data Scientists to build data pipelines for training and serving ML models for Shipt's Personalization Platform
• Work with cross-functional teams (data science, product, backend, DevOps) to define technical solutions and deliver products
• Build scalable, low-latency, and fault-tolerant systems to serve recommendations at scale
• Develop robust APIs and services to deliver real-time or batch recommendations (using Python, Go)
• Integrate ML models into backend services and production applications
• Optimize performance of model inference systems (e.g., using vector databases, caching, distributed serving)
• Build and maintain CI/CD pipelines for model and service deployment
• Leverage modern monitoring/telemetry tools to identify, assess, and provide solutions to platform issues
• Stay up to date with the latest technology trends and bringing the best to the team

Requirements

• 5+ years of experience in machine learning and backend software engineering
• Strong experience building recommendation systems in a real-world production setting
• Proficiency in at least one backend programming language (e.g., Go, Java) and Python
• Deep understanding of recommendation algorithms, user modeling, embeddings, and similarity search
• Experience with ML pipeline tools (e.g., MLflow, Kubeflow, Airflow)
• Familiarity with serving architectures (e.g., REST/gRPC APIs, model servers)
• Strong grasp of distributed systems, microservices, and system design
• Experience with SQL and NoSQL databases and working with large-scale datasets

Nice to have

• Experience with real-time recommendations (e.g., using Kafka, Redis, or Pub/Sub systems).
• Experience with personalization strategies, ranking models, or reinforcement learning.
• Exposure to experimentation platforms and online A/B testing.

We offer

• Flexible working hours (full-time).
• One "Flex Day" off per month – eligible after six months with the company.
• 10 business days of vacation.
• Swiss Medical health coverage.
• Permanent contract with salary review every four months (in ARS).
• Access to Udemy and Platzi for professional training.
• Employee Assistance Program (financial, nutritional, psychological support, etc.).
• Fully covered English classes during working hours.
• Discounts on Club de Beneficios and Samsung products.
• Birthday day off.

About Us
Mobile Computing is joining Grid Dynamics (NASDAQ: GDYN), a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.