Job Overview
We are seeking an experienced ML Ops Technical Product Manager to drive the strategy and roadmap for our ML Ops platform and solutions. In this role, youll collaborate with data science, engineering, and product teams to build scalable and reliable ML infrastructure that accelerates the deployment and monitoring of ML models in production.
Responsibilities
Product Strategy & Roadmap: Define and prioritize the ML Ops product roadmap by assessing business goals, customer needs, and emerging industry trends in ML Ops.
Cross-functional Collaboration: Work closely with data scientists, ML engineers, DevOps, and software engineers to ensure seamless integration and deployment of ML models.
Project Management: Coordinate and manage timelines, resources, and deliverables across multiple teams to keep projects on track.
Model Lifecycle Management: Oversee the end-to-end ML model lifecycle, including data preparation, model development, deployment, monitoring, and maintenance.
Automation & Scaling: Identify opportunities for automation and scalability in the ML pipeline, from data ingestion to model deployment.
Monitoring & Optimization: Develop and implement monitoring and alerting frameworks for model performance and data quality. Partner with engineering teams to troubleshoot and optimize pipelines.
Stakeholder Communication: Serve as the primary point of contact for internal and external stakeholders. Communicate product updates, metrics, and results to senior leadership.
Risk Management: Identify, assess, and mitigate risks related to ML model deployment, including ethical considerations, data privacy, and regulatory compliance.
Documentation & Training: Develop clear and comprehensive documentation for ML Ops processes and workflows. Provide training to teams on best practices.
Required Skills and Qualifications
Bachelors or Masters degree in Computer Science, Data Science, Engineering, or a related field.
5+ years of experience in product management, preferably with a focus on ML Ops, data science, or machine learning infrastructure.
Strong understanding of ML Ops tools and platforms, including ML pipelines, CI/CD, model versioning, and monitoring frameworks.
Technical expertise in machine learning, data engineering, and DevOps methodologies.).
Experience with cloud platforms (AWS, Azure, Google Cloud) and their ML services.
Strong analytical, organizational, and communication skills.
Familiarity with Agile methodologies and project management tools (e.g., Jira,Github).
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to
HR@insightglobal.com.
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https://insightglobal.com/workforce-privacy-policy/ .
Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.