Machine Learning Engineer - Only on W2 Tax Terms
Posted 1 day ago by IT Gig LLC
Negotiable
Undetermined
Remote
Remote
Summary: This role is for a Machine Learning Engineer who will work remotely on a long-term basis under W2 tax terms. The engineer will be responsible for developing and delivering end-to-end machine learning solutions, leading MLOps frameworks, and ensuring compliance with performance and scalability standards. The position requires a strong background in machine learning, MLOps, and cloud platforms, along with experience in production environments.
Key Responsibilities:
- Develop and deliver end-to-end 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 cloud-based systems and ML services.
- Participate in architectural discussions to ensure ML platforms meet compliance, performance, and scalability standards.
- 3+ years of end-to-end 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.
Key Skills:
- Machine Learning Engineer
- MLOps
- Python
- Databricks + Spark
- Cloud Platforms
- HIPAA
- SOC 2
- PHI/PII
Salary (Rate): undetermined
City: undetermined
Country: undetermined
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Machine Learning Engineer
Remote Work
Long Term
Need on W2 Tax Terms :
Key Skills :
- Machine Learning Engineer
- MLOps
- Python
- Databricks + Spark
- Cloud Platforms
- HIPAA
- SOC 2
- PHI/PII
This Machine Learning Engineer is comfortable working with both traditional tabular machine learning models and modern AI techniques, including prompt engineering and LLMbased capabilities.
- 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.
- 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.
Preferred
- 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.