Our partner is a dynamically growing company with a strong international background, leveraging data-driven operations to support advanced analytics and AI/ML-based business processes. Working in a modern technology environment, the company places a strong emphasis on the development and operation of scalable data platforms that drive innovation and business value.
We are looking for a Senior Machine Learning Engineer to join their expanding team.
- Design, build, and operate end-to-end ML pipelines for training, deployment, serving, and monitoring on AWS and Databricks.
- Develop Agentic AI solutions using frameworks such as LangChain, LangGraph, and CrewAI with strong reliability and governance controls.
- Build and optimize feature stores, feature engineering pipelines, and training datasets supporting batch and real-time inference.
- Own and enhance MLOps processes, including CI/CD, automated retraining, model versioning, experiment tracking, and A/B testing.
- Design and implement LLM applications including RAG architectures, prompt management, tool integration, and memory management.
- Establish model monitoring and evaluation frameworks covering performance, drift, accuracy, latency, costs, and system reliability.
- Collaborate with Data Engineering teams to ensure high-quality, reliable data for ML systems.
- Provide technical leadership through mentoring, code reviews, architecture guidance, and technology evaluation.
What we're looking for
- 6+ years in Machine Learning Engineering or Applied ML, with proven production delivery.
- Experience building and operating production ML systems at scale.
- Strong expertise in Databricks ML, AWS, and MLOps practices.
- Hands-on experience with LLMs, RAG pipelines, vector databases, and Agentic AI frameworks (LangChain, LangGraph, AutoGen).
- Strong Python skills and experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, or XGBoost.
- Knowledge of real-time and batch model serving, performance optimization, and cost management.
- Strong software engineering fundamentals including testing, CI/CD, version control, and code reviews.
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