AIMLGen AIMLops Engineer - Mumbai 3-9 years

Responsibilities:
Lead the endtoend 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 SagemakerLlama3 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 crossfunctional 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.
Requirements:
57 years of handson 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.
Endtoend 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 industryspecific challenges.

Preferred:
Familiarity with emerging trends and advancements in MLOps practices. Have experience in working platforms like H2o Rapidminer SagemakerLlama3 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.

Bachelors 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

Junior Resources (36 Years of Experience AI/ML and MLOps developer)

Design and implement cloud solutions build MLOps Pipeline on cloud (AWS Azure or GCP) and onprem setup along with CI/CD Pipelines

Build CI/CD pipelines orchestration by GitLab CI GitHub Actions Circle CI Airflow or similar tools

Develop and implement machine learning algorithms for various projects with a focus on the financial and banking domain. Utilize expertise in bias and variance algorithms to enhance model accuracy and performance

Data science model review run the code refactoring and optimization containerization deployment versioning Testing and Automation and monitoring of Models quality

Collaborate with the legal and compliance teams to navigate AI regulations and ensure adherence to industry standards and regulations to mitigate the AI/ML risks including Bias Drift Variance etc. by tweaking developing and train the model
Communicate with a team of data scientists data engineers and architect document the processes

Stay informed about industry trends and advancements in machine learning.

Required Qualifications:
24 years of handson experience in software development with a focus on machine learning.

Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS MS Azure or GCP) . Well aware with various AI/ML libraries for managing Bias Variance etc.
Experience with MLOps Frameworks like Kubeflow MLFlow DataRobot Airflow etc. experience with Docker and Kubernetes OpenShift

Proficient in various programming languages like Python Go Ruby or Bash good understanding of Linux knowledge of frameworks such as scikitlearn Keras PyTorch Tensorflow etc.

Knowledge of the financial/banking domain with an understanding of relevant industry challenges.
Ability to understand tools used by data scientist and experience with software development and test automation
Fluent in English good communication skills and ability to work in a team

Desired Qualifications:
Bachelors degree in computer science or software Engineering
Experience in using AWS MS Azure or GCP services around AI/ML and MLOps.
Preferred to have any associated Cloud AI/ML Certification