MLOps Engineer - RapidMiner/AWS SageMaker (3-9 yrs)

Responsibilities :

- Lead the end-to-end implementation of MLOps, overseeing the deployment and management of machine learning models, particularly in the financial and banking domain.

- Have experience in working platforms like H2o, Rapidminer, Sagemaker, Llama3, GPT 4.0, Falcon etc.

- Manage and mentor a team of MLOps professionals, ensuring efficient collaboration and successful project delivery.

- Utilize extensive development experience to guide ML algorithm implementations and optimizations.

- Demonstrate expertise in programming languages and ensure AI compliance throughout the MLOps lifecycle.

- Experience in ML orchestration tools like Kubeflow, MLFlow etc.

- Collaborate with cross-functional teams to understand business needs and translate them into effective MLOps solutions.

- Managed implementation around AI/ML regulations, Risk and ensure adherence to industry standards and regulations to mitigate the AI/ML risks including Bias, Drift, Variance etc.

Qualifications :

- 3-9 years of hands-on experience in software development, with a focus on MLOps implementation.

- Proven team management experience, with the ability to lead and mentor a group of MLOps professionals.

- Demonstrated expertise in ML algorithm implementation and optimization.

- Proficiency in programming languages (Python, R etc.) used in MLOps, with a strong understanding of AI compliance.

- End-to-end implementation experience in MLOps, from model development to deployment and monitoring.

- Experience in ML orchestration tools like Kubeflow, MLFlow etc.

- Advantage with experience on data engineering tools/platforms like Apache Kafka, Trino, Druid.

- Knowledge of the financial/banking domain, with an understanding of industry-specific challenges.

Preferred Skills :

- Familiarity with emerging trends and advancements in MLOps practices.

- Have experience in working platforms like H2o, Rapidminer, Sagemaker, Llama3, GPT 4.0, Falcon etc.

- Experience in addressing compliance/regulatory concerns (Bias, Drift, Explainability, AI fairness etc.) related to AI/ML specific to the financial industry.

Required Skills :

- Bachelor's degree in Computer Science or Software Engineering.

- Experience in using AWS, MS Azure or GCP services around AI/ML and MLOps.

- Advantage with experience on data engineering tools/platforms like Apache Kafka, Trino, Druid, Spark etc.

- Preferred to have any associated Cloud, AI/ML Certification.