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.
Essential functions
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
Qualifications
- 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
Would be a plus
- 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.Apply to the position
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Grid Dynamics is an equal opportunity employer. We are committed to creating an inclusive environment for all employees during their employment and for all candidates during the application process.
All qualified applicants will receive consideration for employment without regard to, and will not be discriminated against based on, age, race, gender, color, religion, national origin, sexual orientation, gender identity, veteran status, disability or any other protected category. All employment is decided on the basis of qualifications, merit, and business need.

