Machine Learning Engineer

About the Role

Dice is the leading career destination for technology experts. Our client, IT Gig LLC, is actively seeking a talented Machine Learning Engineer who can thrive on W2 tax terms in a remote setting.

Key Responsibilities:

• Develop and deliver end-to-end machine learning solutions, from defining technical requirements to architecting scalable systems.
• Implement robust monitoring, logging, and maintenance workflows for production models.
• Lead the design of MLOps frameworks, including CI/CD integration, model registry management, feature stores, drift detection, and automated retraining strategies.
• Create custom API integrations to ensure seamless connectivity between cloud-based systems and ML services.
• Participate in architectural discussions to guarantee that ML platforms meet strict compliance (HIPAA/SOC 2), performance, and scalability standards.

Required Qualifications:

• ML Experience: Comfortable working with both traditional tabular models and modern AI techniques, including prompt engineering and LLM-based capabilities.
• Production Readiness: 3+ years of end-to-end ML development experience covering data prep, feature engineering, modeling, calibration, deployment, monitoring, and maintenance.
• MLOps Expertise: 3+ years building production pipelines with CI/CD integration, drift detection, and automation.
• Coding Skills: Strong proficiency in Python for production ML (testing, packaging, type hints) and SQL. Scala experience is a plus.
• Cloud & Distributed Compute: 2+ years working with distributed compute environments like Spark/Databricks on Azure, AWS, or Google Cloud Platform.

Preferred Qualifications:

• Databricks and infrastructure/networking experience.
• 1+ years implementing LLM-based solutions in production (prompt/response design, safety guardrails, latency/cost optimization).
• Experience designing compliant ML platforms for PHI/PII governance under HIPAA/SOC 2 standards.