Senior Machine Learning Engineer
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Requirements
• 4+ years of experience in machine learning engineering, building production-grade ML systems. • machine learning engineering • Hands-on experience with agentic AI frameworks (e.g., LangGraph, LlamaIndex, Zep, Mem0, Langfuse, LangSmith). • agentic AI frameworks • Experience building RAG pipelines, recommendation systems, and/or vector search applications (e.g., Pinecone, Vespa, PostgreSQL + pgvector). • RAG pipelines • vector search • Strong background in time-series modeling, anomaly detection, and large-scale data analysis (e.g., Clickhouse). • time-series modeling • Skilled in asynchronous API design, containerization, and modern CI/CD workflows (FastAPI, Docker, Kubernetes, GitHub/Bitbucket). • asynchronous API design • Excellent EDA skills with the ability to translate data insights into production-ready ML solutions. • Comfortable working with LLM ambiguity, designing systems that fail gracefully and learn continuously. • LLM ambiguity • Proactive, independent, and curious—able to own complex features end-to-end and raise the technical bar for the team. • Strong communication skills—able to explain trade-offs between AI approaches and align technical metrics to business goals. • Experience leveraging AI tools and functionality to improve workflow efficiency, research, and experimentation. • AI tools and functionality • Our values: • Our values: • At Foam, diversity, equity, and inclusion (DEI) isn't just a statement, it's our collective strength. Our people are our superpower. A diverse team and inclusive leadership have shaped Whalar since our inception in 2016, fueling a constant evolution of growth. We champion a culture of respect and empathy, fostering a sense of belonging that transcends demographics. We hire individuals of all backgrounds and empower them to thrive, challenge stereotypes, and actively break societal barriers.
Responsibilities
• Design and deploy autonomous AI agents, including reasoning loops, memory layers, and orchestration pipelines. • autonomous AI agents • Build observability and evaluation systems to monitor reasoning, token usage, and model performance, ensuring reliable production behavior. • observability and evaluation systems • Lead the development of multimodal ML pipelines for semantic search, RAG, recommendation systems, and vector search across text, image, and video data. • multimodal ML pipelines • Engineer high-throughput time-series analytics and forecasting models that connect batch OLAP queries with real-time inference. • high-throughput time-series analytics and forecasting models • Develop and maintain scalable asynchronous APIs and containerized services, ensuring reliability, monitoring, and performance optimization. • scalable asynchronous APIs • Partner with product and engineering teams to translate business goals into measurable ML outcomes. • Drive research-to-production pipelines for experimental AI projects and evaluate emerging technologies to advance our platform. • research-to-production pipelines
Benefits
• Foam provides flexible benefits and collaborative work environments/experiences, so employees can work productively in a setting that best and uniquely suits their needs. • Private medical insurance • Health cash plan • 25 days of PTO + Sick days + Winter break • Private pension scheme • Monthly phone/internet reimbursement • Professional development stipend • New joiner Home office allowance • Enhanced maternity (22 weeks)/paternity (16 weeks) leave • Reduced fee gym membership (next to office location)