Machine Learning Engineer

About role:

We have an opening for a Machine Learning Engineer (MLE) role, who will be responsible for guiding the successful development, automation and governance of AI/ML Solutions to the internal customers. The MLE will be responsible for collaborating with Data Scientists, Domain Experts and Product Owners to build and deploy the end-to-end AI Products for the company. The role will require working knowledge of Cloud, DevOps/ MLOps, Machine Learning, Deep Learning and Application Development. This position will also be involved in the formulation of key business requirements to be solved and rationalizing the various best practices to solve those problems.

Key responsibilities:

• Script production-ready codes
• Leveraging GPU & CPU resources as appropriate / understanding capacity requirements for ML Workloads
• Architect, automate and orchestrate Dev-Ops/ ML-Ops pipelines on cloud
• Craft re-usable tools and frameworks to monitor, optimize and maintain ML solutions
• Understand business problems and collaborate within the team to ensure scalability, business continuity and appropriate turnaround time
• Conduct internal workshops and external meetups, participate in external conferences, and give talks
• Continuously evolve your craft by keeping up to date with the new developments in AI/ML and related technologies and upskilling on these as needed.

Qualifications and Requirements:

• A bachelor's or master’s degree in Computer Science, Operations Research, Mathematics and Computing with 3-4 years of relevant experience
• In-depth Understanding of key Machine Learning & Deep Learning Algorithms
• Experience of working with large data sets, coming from varied sources
• Excellent Programming Skills (Python Preferred)
• Experience in Cloud Application Development (Google Cloud Platform & Azure Preferred)
• Solid understanding of Deep learning platforms such as Keras, Tensor-flow and/or PyTorch is highly desirable
• Great at solving problems; debugging; troubleshooting; and designing & implementing solutions to complex technical issues
• Experience working with deployment & cloud orchestration tools (such as Airflow, Kubeflow, Seldon, SonarQube, Jenkins etc.)
• Proficiency in a Unix/Linux environment for automating processes with shell scripting
• Hands on experience of designing, building, and supporting RESTful APIs

Good to have:

• Knowledge of Oilfield terminology and business practices
• Experience with IoT/ Edge technology is a plus
• Hands on experience of designing, building, and supporting RESTful APIs
• Recognized open-source contributions
• Familiarity with data engineering tools (Flink/Spark/Kafka etc.)
• Experience with big data stack (Spark, Hadoop, Storm, Hive & Pig) and NoSQL stores is a plus