Senior Associate, MLOps (Data/DevOps) Engineer

Summary of the Position:

Looking for a Sr MLOps Engineer with a strong background in Data Engineering, who aspire to be part of a Data Science & AI Operations function in R&D. This role involves applying advanced software engineering skills for the design, creation, management, and business use of large datasets, across a variety of Data/ML platforms. This is an ideal opportunity for individuals with a passion for applying DevOps Skills for AI/ML application development in the health-care sector.

Preferred Requirements:

• M.S (preferred) or Ph.D. in Computer Science, Data Science, or related quantitative fields.

• Proven experience in applying advanced software engineering skills in Data Science platforms (Data/ML)

• Strong experience in using MLOps tools like AWS SageMaker, MLFlow and ML Frameworks like TensorFlow/PyTorch

• Hands-on Experience in CI/CD using tools Terraform/CloudFormation, Git, Containers – Docker/Kubernetes, ECS/EKS, Helm Charts

• Strong knowledge and Hands-on Experience with Data Lakes in building Data Pipelines using Python, Apache Spark, Lambda, Step Functions, SQL, Glue ETL in AWS

• Working knowledge on Cloud Platforms & Infrastructure in AWS

• Programming and Scripting knowledge using Python (Must needed), CLI/SDK/CDK

• Ability to balance between Development and Research work on latest trends (GenAI Ops)

Minimum Requirements:

• Master’s Degree or Higher in Computer Science/Data Science

• The ability to fluently read, write, understand, and communicate in English.

• Relevant AWS Certifications related to ML/Data /Data (prefered)

• 3+ years of hands-on working experience in applying MLOps engineering for Data/AI with real-world problem solving in the medical device industry or equivalent industry experience is preferred.

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Alcon is an Equal Opportunity Employer and takes pride in maintaining a diverse environment. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, gender identity, marital status, disability, or any other reason.