Senior Machine Learning Engineer (GenAI / Production Systems) – 100% Remote | Direct Hire
We are seeking a Senior Machine Learning Engineer to join a high-impact, enterprise AI initiative focused on building production-grade machine learning and generative AI systems in a complex, data-rich environment.
This is a full-time, direct hire position (no C2C) working on real-world systems that require scalability, reliability, and measurable business impact—not experimental or research-only work.
• Must have hands-on experience building and deploying ML systems in production
• Must have experience working with sensitive, regulated, or compliance-driven data environments
• No third-party submissions / no C2C
What You’ll Be Doing
• Design and build end-to-end ML pipelines (data ingestion → feature engineering → model training → deployment → monitoring)
• Develop and deploy LLM / GenAI solutions (RAG, NLP, prompt engineering, vector search)
• Work with large, complex structured and unstructured datasets
• Build scalable, production-ready services using modern cloud infrastructure
• Partner with stakeholders to translate real business problems into ML solutions
• Implement model monitoring, drift detection, and retraining strategies
What We’re Looking For
• 5+ years of experience as a Machine Learning Engineer (not just Data Scientist/Analyst)
• Strong experience with Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn)
• Hands-on experience with:
• ML pipelines / MLOps (CI/CD, model deployment, monitoring)
• Cloud platforms (AWS, Azure, or Google Cloud Platform)
• Containerization (Docker, Kubernetes preferred)
• Experience with GenAI / LLMs (RAG, embeddings, vector databases, LangChain, etc.)
• Experience working with regulated or high-sensitivity data environments (financial, healthcare, gov, etc.)
• Strong communication skills and ability to work cross-functionally
To Be Considered, Please Include:
(Resumes without this will NOT be reviewed)
In your resume or submission, briefly describe:
• A production ML system you built and deployed (what problem it solved, scale, tools used)
• A GenAI / LLM use case you’ve implemented (RAG, NLP, etc.)
• The type of data environment you worked in (regulated, high-compliance, etc.)
Why This Role
• Work on real-world ML systems at scale
• High visibility, high impact work
• Collaborative, engineering-focused team
• 100% remote
• Permanent / direct hire
• Salary: $135,000 – $150,000
This is a full-time, direct hire position (no C2C) working on real-world systems that require scalability, reliability, and measurable business impact—not experimental or research-only work.
• Must have hands-on experience building and deploying ML systems in production
• Must have experience working with sensitive, regulated, or compliance-driven data environments
• No third-party submissions / no C2C
What You’ll Be Doing
• Design and build end-to-end ML pipelines (data ingestion → feature engineering → model training → deployment → monitoring)
• Develop and deploy LLM / GenAI solutions (RAG, NLP, prompt engineering, vector search)
• Work with large, complex structured and unstructured datasets
• Build scalable, production-ready services using modern cloud infrastructure
• Partner with stakeholders to translate real business problems into ML solutions
• Implement model monitoring, drift detection, and retraining strategies
What We’re Looking For
• 5+ years of experience as a Machine Learning Engineer (not just Data Scientist/Analyst)
• Strong experience with Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn)
• Hands-on experience with:
• ML pipelines / MLOps (CI/CD, model deployment, monitoring)
• Cloud platforms (AWS, Azure, or Google Cloud Platform)
• Containerization (Docker, Kubernetes preferred)
• Experience with GenAI / LLMs (RAG, embeddings, vector databases, LangChain, etc.)
• Experience working with regulated or high-sensitivity data environments (financial, healthcare, gov, etc.)
• Strong communication skills and ability to work cross-functionally
To Be Considered, Please Include:
(Resumes without this will NOT be reviewed)
In your resume or submission, briefly describe:
• A production ML system you built and deployed (what problem it solved, scale, tools used)
• A GenAI / LLM use case you’ve implemented (RAG, NLP, etc.)
• The type of data environment you worked in (regulated, high-compliance, etc.)
Why This Role
• Work on real-world ML systems at scale
• High visibility, high impact work
• Collaborative, engineering-focused team
• 100% remote
• Permanent / direct hire
• Salary: $135,000 – $150,000