Machine Learning
2 months ago
Job Title: Senior Engineer –Machine Learning (MLOps)
Experience : 2+ Years
Location Options: Gurgaon / Manyata Tech Park- Bangalore
Job Details and Requirements:
Overview: We are seeking a skilled and experienced Senior Engineer – Machine Learning to join our team. The ideal candidate will have a strong background in end-to-end machine learning model lifecycle management, including model development, deployment, and operations. You will be responsible for designing and implementing MLOps solutions to scale machine learning models efficiently, especially within large, data-intensive applications. You will play a key role in enhancing MLOps capabilities for high-profile clients in the pharma industry, ensuring seamless production and operationalization of complex models.
Qualifications:
Bachelor’s degree in Information Technology, Computer Science, or a related field.
Certifications and specialized training in Data Science, Machine Learning, MLOps, NLP, and other relevant fields are highly preferred.
Languages/Tools: Python, Git, MySQL, Plotly, Streamlit
Cloud/Platforms: AWS (SageMaker), Dataiku DSS, Snowflake
Containerization/Orchestration: Kubernetes
Visualization Tools: Tableau, Plotly
ML Techniques: Experience with modern ML algorithms, NLP, and Deep Learning.
Experience and Skills:
MLOps Implementation: Proven experience in designing and deploying MLOps solutions for multiple use cases (preferably in the pharma industry), including the use of cloud technologies, orchestration tools, and monitoring frameworks.
Model Deployment: Experience operationalizing large-scale machine learning models in production, optimizing processes for dynamic targeting and scalability.
Technical Expertise: Proficiency in Python, AWS SageMaker, Dataiku DSS, Snowflake, Kubernetes, MySQL, Git, and other relevant tools for data engineering and model deployment.
Problem-Solving: Strong analytical skills and ability to optimize and scale machine learning pipelines and code, reducing manual efforts and operational complexities.
Collaboration and Communication: Experience working with cross-functional teams across geographies, strong interpersonal and communication skills for working with stakeholders and technical teams.
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