Lead ML/AI Platform Engineer
New
S
SavvyMoneyFinancial Technology
Warsaw, Poland, overlap with US Pacific business hoursContractLead
Salary not disclosed
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Job Details
- Experience
- 8+ years in software or ML engineering, including 5+ years shipping production ML systems
- Required Skills
- PythonSQLJavaMachine LearningPyTorchSparkMLOpsGenerative AI
Requirements
- 8+ years in software or ML engineering.
- 5+ years shipping production ML systems with a track record of owning high-scope problems.
- Technical leadership experience, including mentoring senior engineers and driving architectural strategy.
- Hands-on experience with AWS managed ML stack (SageMaker, Bedrock, AgentCore).
- Proficiency with open-source ML tools (JupyterLab, Spark, MLflow).
- Deep expertise in Python and the core ML stack (scikit-learn, pandas, NumPy, PyTorch/TensorFlow, XGBoost/LightGBM).
- Production experience with GenAI/LLMs, including RAG, evaluation, and safety/cost trade-offs.
- Working knowledge of Java for service code review, API contracts, and debugging.
- Deep working knowledge of AWS infrastructure (S3, Athena, Redshift, Glue, Lambda) and SQL.
- Ability to operate as an independent contractor through your own entity or an approved arrangement.
- Ability to maintain overlap with US Pacific business hours.
Responsibilities
- Partner with the Data Platform Architect to define AI/ML architecture, tooling, and build-vs-buy strategy.
- Own the ML/AI platform including training infrastructure, model serving, inference pipelines, and production integration.
- Develop feature engineering, model training, and hosted inference using Amazon SageMaker.
- Drive GenAI/LLM strategies including RAG, prompt engineering, and agentic workflows using Amazon Bedrock and AgentCore.
- Define API contracts and integrate ML services with Java microservices while managing latency and throughput.
- Lead the implementation of guardrails for agentic workflows in a regulated financial environment.
- Partner with Data Scientists to productionize models and shorten deployment loops.
- Represent the AI/ML function in cross-functional forums to align technical and non-technical stakeholders.
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