Job Details

Client is seeking a highly experienced Python Engineer to join our FSD Product Development team. This individual will lead the design and implementation of scalable, secure, and resilient big data and MLOps platforms and APIs. The ideal candidate will have extensive experience in AWS, Python,and MLOps frameworks, and will work closely with cross-functional teams to build platforms that support timely, accurate, and relevant data delivery across Client's products and services.

Job Responsibilities:

• Collaborate with Architecture, Product, CloudOps, and Engineering teams to design scalable and flexible cloud architectures using AWS
• Lead implementation of complex architectural solutions based on AWS design principles and best practices
• Build scalable, cost-efficient ML pipelines using Python, AWS SageMaker, Lambda, Step Functions, Docker, ECS/Fargate, and related tools
• Drive architectural reviews, best practice implementation, and document design at both high and low levels
• Define and enforce code quality and test coverage standards
• Communicate architectural decisions across product and engineering teams
• Drive continuous improvement and performance enhancements across systems
• Lead proof-of-concept projects for new technology integrations
• Mentor and guide junior team members
• Conduct system integration, monitor system health, and implement recovery strategies
• Participate in business requirement analysis and cross-functional discussions
• Ensure software and infrastructure meet security and compliance requirements

• 8+ years in engineering roles including software architect or technical lead
• 5+ years of experience with AWS cloud services (EKS, Lambda, S3, RDS, Aurora, Fargate, etc.)
• Expertise in Python frameworks: Flask, Django, AsyncIO
• Strong hands-on experience with MLOps platforms (e.g., AWS SageMaker, Kubeflow, MLflow)
• Deep understanding of distributed software systems, APIs, microservices, and real-time systems
• Experience in CI/CD (e.g., Jenkins, CodePipeline, Harness)
• Familiar with logging/messaging systems like Kafka, RabbitMQ, SQS
• Working knowledge of monitoring tools and cloud performance tuning
• Excellent problem-solving, analytical, and communication skills
• Ability to work with globally distributed teams in Agile/Scrum environments

• MS in Computer Science or related field
• Experience with ML frameworks: TensorFlow, PyTorch, Scikit-learn
• Experience with orchestration tools like Kubeflow, MLflow, Airflow
• Familiarity with monitoring tools like Dynatrace, Splunk
• Experience building automated pipelines for analytics
• Knowledge of AWS Well-Architected Framework and best practices

Bachelor's degree in computer science or related field; Master's degree preferred

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