ML-Ops Engineer
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Job Location:
Concord, CA - USA
Monthly Salary:
Not Disclosed
Posted on:
2 hours ago
Vacancies:
1 Vacancy
Job Summary
Job Title: ML-Ops Engineer
Location: Concord CA (Onsite)
Duration: Long-Term Contract
Interview Process: Client Round In-person (Lets Target only locals and willing to go for in-person interview at Clients location)
Overview:
- Tachyon Cortex Machine Learning AI team seeking a ML Ops Engineer to drive the full lifecycle of machine learning solutions.
Key Responsibilities:
- Develop and maintain ML pipelines using tools like MLflow Kubeflow or Vertex AI.
- Automate model training testing deployment and monitoring in cloud environments (e.g. GCP AWS Azure).
- Implement CI/CD workflows for model lifecycle management including versioning monitoring and retraining.
- Monitor model performance using observability tools and ensure compliance with model governance frameworks (MRM documentation explainability)
- Collaborate with engineering teams to provision containerized environments and support model scoring via low-latency APIs
- Leverage Auto ML tools (e.g. Vertex AI Auto ML H2O Driverless AI) for low-code/no-code model development documentation automation and rapid deployment
Qualifications:
- 10 Years of professional experience in Software Engineering & 3 Years in AIML Machine Learning Model Operations.
- Strong proficiency in Java and Python SQL and ML libraries (e.g. scikit-learn XGBoost TensorFlow PyTorch).
- Experience with cloud platforms and containerization (Docker Kubernetes).
- Familiarity with data engineering tools (e.g. Airflow Spark) and ML Ops frameworks.
- Solid understanding of software engineering principles and DevOps practices.
- Ability to communicate complex technical concepts to non-technical stakeholders.
