Job highlights

- Masters/PhD in CSE/IT from Tier 1 institute with 12+ years in data and analytics; expertise in MLOps tools (MLflow, Kubeflow, TFX, SageMaker), containerization (Docker, Kubernetes, Helm), and data engineering tools (Airflow, Kafka, Snowflake, Hadoop)
- Design and deliver scalable MLOps and data science solutions, engage clients for business growth, mentor teams, develop best practices, and drive innovation in pharma AI applications

Job Summary - MLOPs (Director)

Experience - 12+ yrs.

Job Location - Noida / Gurgaon / Bangalore

Must have skills & competencies

- Experience in designing innovative solutions which are aligned with client expectations and requirements and that has been helpful in crafting winning proposals in the field of MLOPS/Data Engineering and Data Science.
- Good experience in developing, delivering and operationalizing scalable processes for large and complex client engagements in the field of Data science.
- Engage with clients to grow and deliver business. Ensure profitable delivery and outstanding customer experience by designing end-to-end solutions and guiding the team to deliver as per established processes.
- Develop and operationalize scalable processes to deliver on large and complex client engagements.
- Train and mentor staff and establish best practices and ways of working to enhance data science capabilities at Axtria. Operationalize an ecosystem for continuous learning and development.
- Write white papers,



collaborate with academia and participate in relevant speaker opportunities to continuously upgrade learning and establish Axtria's thought leadership in this space.
- Research, develop, evaluate and optimize newly emerging algorithms and technologies for relevant use cases in pharma commercial & clinical space.
- Strong expertise in MLOps tools and practices, including CI/CD pipelines, automated testing, model versioning, and monitoring using MLflow, Kubeflow, TFX, or SageMaker. Experience with containerization and orchestration technologies like Docker, Kubernetes, and Helm for scalable model deployment.
- Strong understanding of data engineering principles and tools, such as Apache Airflow, Kafka, Snowflake, or Hadoop, for managing data pipelines.
- Proven experience in integrating explainability and fairness tools, such as SHAP, LIME, or Fairlearn, into ML systems.

Good to have skills & competencies

- Proven ability to collaborate with cross-functional teams, including product managers, data scientists, and DevOps engineers, to deliver end-to-end generative AI solutions.
- Proven experience in leading teams focused on generative AI projects, mentoring ML engineers, and driving innovation in AI applications.
- Possessing robust analytical skills to address and model intricate business needs is highly advantageous, especially for those with a background in life sciences or pharmaceuticals.

Eligibility Criteria

- Masters/PhD in CSE/IT from Tier 1 institute
- Minimum 12+ years of relevant experience in building software applications in data and analytics field.

📌 Director (Noida)
🏢 Axtria
📍 Noida