Machine Learning Engineer - MLOps

Role: Machine Learning Engineer - MLOps

Job Overview

As a Senior Software Development Engineer, Machine Learning (ML) Operations in the Technology & Engineering division, you will be responsible for enabling PitchBook’s Machine Learning teams and practitioners by providing tools that optimize all aspects of the Machine Learning Development Life Cycle (MLDLC). Your work will support projects in a variety of domains, including Generative AI (GenAI), Large Language Models (LLMs), Natural Language Processing (NLP), Classification, and Regression.

Team Overview

Your team’s goal will be to reduce friction and time-to-business-value for teams building Artificial Intelligence (AI) solutions at PitchBook. You will be essential in helping to build exceptional AI solutions relied upon and used by thousands of PitchBook customers every day. You will work with PitchBook professionals around the world with the collective goal of delighting our customers and growing our business.

While demonstrating a growth mindset, you will be expected to continuously develop your expertise in a way that enhances PitchBook’s AI capabilities in a scalable and repeatable manner. You will be able to solve various common challenges faced in the MLDLC while providing technical guidance to less experienced peers.

Outline Of Duties And Responsibilities

• Serve as a force multiplier for development teams by creating golden paths that remove roadblocks and improve ideation and innovation
• Collaborate with other engineers, product managers, and internal stakeholders in an Agile environment
• Design and deliver on projects end-to-end with little to no guidance
• Provide support to teams building and deploying AI applications by addressing common painpoints in the MLDLC
• Learn constantly and be passionate about discovering new tools, technologies, libraries, and frameworks (commercial and open source), that can be leveraged to improve PitchBook’s AI capabilities
• Support the vision and values of the company through role modeling and encouraging desired behaviors.
• Participate in various cross-functional company initiatives and projects as requested.
• Contribute to strategic planning in a way that ensures the team is building exceptional products that bring real business value.
• Evaluate frameworks, vendors, and tools that can be used to optimize processes and costs with minimal guidance.
  
  
  

Experience, Skills And Qualifications

• Degree in Computer Science, Information Systems, Machine Learning, or a similar field preferred (or commensurate experience)
• +2 years of experience in hands-on development of Machine Learning algorithms
• +2 years of experience in hands-on deployment of Machine Learning services
• +2 years of experience supporting the entire MLDLC, including post-deployment operations such as monitoring and maintenance
• +2 years of experience with Amazon Web Services (AWS) and/or Google Cloud Platform (GCP)
• Experience with at least 80%: PyTorch, Tensorflow, LangChain, scikit-learn, Redis, Elasticsearch, Amazon SageMaker, Google Vertex AI, Weights & Biases, FastAPI, Prometheus, Grafana, Apache Kafka, Apache Airflow, MLflow, KubeFlow
• Ability to break large, complex problems into well-defined steps, ensuring iterative development and continuous improvement
• Experience in cloud-native delivery, with a deep practical understanding of containerization technologies such as Kubernetes and Docker, and the ability to manage these across different regions.
• Proficiency in GitOps and creation/management of CI/CD pipelines
• Demonstrated experience building and using SQL/NoSQL databases
• Demonstrated experience with Python (Java is a plus) and other relevant programming languages and tools.
• Excellent problem-solving skills with a focus on innovation, efficiency, and scalability in a global context.
• Strong communication and collaboration skills, with the ability to engage effectively with internal customers across various cultures and regions.
• Ability to be a team player who can also work independently
• Experience working across multiple development teams is a plus
  
  
  

Working Conditions

The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.

Morningstar India is an equal opportunity employer

Morningstar’s hybrid work environment gives you the opportunity to work remotely and collaborate in-person each week. We’ve found that we’re at our best when we’re purposely together on a regular basis, at least three days each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you’ll have tools and resources to engage meaningfully with your global colleagues.

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