MLOps Engineer
1 month ago
Job Title : Sr. MLOps Engineer
Primary skills: Expertise in AI/ analytics product & solution delivery
Location : Hyderabad
Mode of work : On Site
Experience : 3-6 years
About the job
We are looking for a highly skilled and experienced MLOps Engineer who will play a pivotal role in bridging the gap between machine learning and operational excellence within a Advanced Analytics team. By automating the deployment, monitoring, and maintenance of machine learning models, this role ensures that data-driven insights are seamlessly integrated into business processes. Collaboration with data scientists and engineers, the ML Ops Engineer enhances model performance, scalability, and reliability. Drive efficiency and innovation, fosters a culture of continuous improvement, enabling the organization to leverage machine learning for data decision-making.
Know your team.
At Value Momentum, we've strategically established an Advanced Analytics Center in to bolster our AI and Analytics capabilities in the Property & Casualty (P&C) Insurance sector. This unit is dedicated towards revolutionizing the P&C Insurance with cutting-edge AI and analytics solutions. Advanced Analytics Center plays a pivotal role in company’s overall IT consulting and services talent strategy, with a focus on capability development, fostering reusability, and stimulating experimentation and innovation.
Our work environment is dynamic, intellectually stimulating, and seamlessly combines capability development with service delivery. Comprising a diverse team of data scientists, analysts, and consultants specializing in analytics, we offer a distinctive blend of industry expertise, AI proficiency, and top-tier technologies. By collaborating with business verticals, engineering centers, and our clients, Advanced Analytics team delivers state-of-the-art AI/analytics solutions across the P&C value chain – Product/Underwriting, Claims, Distribution, and Enterprise IT.
Responsibilities:
Evaluate and source appropriate cloud infrastructure solutions for machine learning needs, ensuring cost-effectiveness and scalability based on project requirements.
Automate and manage the deployment of machine learning models into production environments, ensuring version control for models and datasets using tools like Docker and Kubernetes.
Set up monitoring tools to track model performance and data drift, conduct regular maintenance, and implement updates for production models.
Work closely with data scientists, software engineers, and stakeholders to align on project goals, facilitate knowledge sharing, and communicate findings and updates to cross-functional teams.
Design, implement, and maintain scalable ML infrastructure, optimizing cloud and on-premise resources for training and inference.
Document ML processes, pipelines, and best practices while preparing reports on model performance, resource utilization, and system issues.
Provide training and support for team members on ML Ops tools and methodologies, and stay updated on industry trends and emerging technologies.
Diagnose and resolve issues related to model performance, infrastructure, and data quality, implementing solutions to enhance model robustness and reliability.
Requirements:
3-6 years of relevant experience in AI/ analytics product & solution delivery
Bachelor’s/Master’s degree in an information technology/computer science/ Engineering or equivalent fields experience.
Proficiency in frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Strong skills in Python and/or R; familiarity with Java, Scala, or Go is a plus.
Experience with cloud services such as AWS, Azure, or Google Cloud Platform, particularly in ML services (e.g., AWS SageMaker, Azure ML).
CI/CD tools (e.g., Jenkins, GitLab CI), containerization (e.g., Docker), and orchestration (e.g., Kubernetes).
Experience with databases (SQL and NoSQL), data pipelines, ETL processes, ML pipeline orchestration (Airflow)
Familiarity with monitoring and logging tools such as Prometheus, Grafana, or ELK stack.
Proficient in using Git for version control.
Strong analytical and troubleshooting abilities to diagnose and resolve issues effectively.
Good communication skills for working with cross-functional teams and conveying technical concepts to non-technical stakeholders.
Ability to manage multiple projects and prioritize tasks in a fast-paced environment.
Preferred:
Familiarity of new age AI and ML techniques such as GenAI, foundational models, large language models (LLMs) and applications
Relevant certifications in cloud platforms, machine learning, or data science (e.g., AWS Certified Machine Learning, Azure Data Engineer).
Prior experience in MlOps
Prior experience in P&C Insurance
About ValueMomentum
ValueMomentum is a leading solutions provider for the global property & casualty insurance industry, supported by deep domain and technology capabilities. We offer a comprehensive suite of advisory, development, implementation, and maintenance services across the entire P&C insurance value chain. This includes Underwriting, Claims, Distribution, and more, empowering insurers to stay ahead with sustained growth, high performance, and enhanced stakeholder value. Trusted by over 75 insurers, ValueMomentum is one of the largest standalone insurance-focused solutions providers to the US insurance industry.
Our culture – Our fuel
At ValueMomentum, we believe in making employees win by nurturing them from within, collaborating and looking out for each other.
People first - Empower employees to succeed.
Nurture leaders - Nurture from within.
Enjoy wins – Recognize and celebrate wins.
Collaboration – Foster a culture of collaboration and people-centricity.
Diversity – Committed to diversity, equity, and inclusion.
Fun – Create a fun and engaging work environment.
Warm welcome – Provide a personalized onboarding experience.
Company Benefits
Compensation - Competitive compensation package comparable to the best in the industry.
Career Growth - Career development, comprehensive training & certification programs, and fast track growth for high potential associates.
Benefits: Comprehensive health benefits and life insurance.
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