[Remote] Machine Learning Engineer - Only on W2 Tax Terms

Note: The job is a remote job and is open to candidates in USA. Dice is a recruiting company seeking a Machine Learning Engineer for a long-term remote contract position. The role involves developing and delivering end-to-end machine learning solutions, leading MLOps framework design, and ensuring compliance and scalability of ML platforms.

Responsibilities

• Develop and deliver endtoend machine learning solutions, including defining technical requirements, architecting scalable systems, and implementing monitoring, logging, and maintenance workflows
• Lead the design and implementation of MLOps frameworks, including pipeline development, CI/CD integration, drift detection, retraining workflows, and rollback strategies
• Develop and customize API integrations to enable seamless connectivity between cloudbased systems and ML services
• Participate in architectural discussions to ensure ML platforms meet compliance, performance, and scalability standards

Skills

• Machine Learning Engineer
• MLOps
• Python
• Databricks + Spark
• Cloud Platforms
• HIPAA
• SOC 2
• PHI/PII
• 3+ years of endtoend ML development in production (data prep, feature engineering, modeling, calibration, deployment, monitoring, maintenance)
• 3+ years of MLOps experience building production pipelines (CI/CD, model registry, feature store), implementing monitoring & drift detection, and automating retraining
• 3+ years of Python for production ML (testing, packaging, type hints, linting) and SQL for analytical and production workloads; Scala a plus
• 2+ years working with distributed compute and cloud ML environments (e.g., Spark/Databricks on Azure/AWS/Google Cloud Platform) and modern data ecosystems (data lakes, DBMS)
• Strong debugging and optimization skills across data and ML workflows
• Track record of ownership and problem solving driving measurable impact and quality under ambiguity and evolving requirements
• 1+ years of Databricks experience + some experience in infrastructure/networking
• 1+ years implementing LLMbased solutions in production (prompt/response design, evaluation frameworks, guardrails/safety, latency/cost optimization)
• 1+ years designing compliant ML platforms (e.g., HIPAA, SOC 2) and working with PHI/PII governance, access controls, and auditability

Company Overview