MLOps Engineer

World Wide Technology; St. Louis (MO); Remote; USD 80,000 - 120,000; Full time

Job summary

Join a forward-thinking company as an MLOps Engineer, where innovation meets collaboration. This role offers the chance to develop, deploy, and operationalize cutting-edge AI and ML solutions while working in cross-functional agile teams. You'll be at the forefront of technology, mentoring fellow engineers and data scientists, and advocating for scalable analytics solutions. With a strong culture and robust benefits, this established industry player is dedicated to fostering a collaborative environment that empowers you to make a significant impact in the world of technology. If you're passionate about AI and MLOps, this opportunity is perfect for you.

Benefits

Health and wellbeing programs

Financial perks

Paid time off

Legal insurance

Pet insurance

Qualifications

• Experience with ML lifecycle and collaboration with data scientists.
• Proficiency in programming languages common to data science.

Responsibilities

• Develop and operationalize scalable AI & ML solutions.
• Mentor data scientists and engineers on software development best practices.

Skills

Continuous Integration/Continuous Delivery

MLOps tools (Domino Data Labs, Dataiku, mlflow, AzureML, Sagemaker)

Programming languages (Python, SQL)

LLM platforms (OpenAI, Bedrock, NVAIE)

Cloud providers (Azure, AWS, GCP)

Agile and DevOps methodologies

Communication skills

Tools

TensorFlow

Keras

PyTorch

Caffe

Snowflake

Fabric

Job description

Qualifications:

• Experience applying continuous integration/continuous delivery best practices, including Version Control, Trunk Based Development, Release Management, and Test-Driven Development.
• Experience with popular MLOps tools (e.g., Domino Data Labs, Dataiku, mlflow, AzureML, Sagemaker) and frameworks (e.g., TensorFlow, Keras, Theano, PyTorch, Caffe).
• Experience with LLM platforms (OpenAI, Bedrock, NVAIE) and frameworks (LangChain, LangFuse, vLLM).
• Proficiency in programming languages common to data science such as Python and SQL.
• Understanding of LLMs and supporting concepts (tokenization, guardrails, chunking, Retrieval Augmented Generation).
• Knowledge of the ML lifecycle (data wrangling, model selection, training, validation, deployment) and experience collaborating with data scientists.
• Familiarity with at least one major cloud provider (Azure, AWS, GCP), including resource provisioning, connectivity, security, autoscaling, and Infrastructure as Code (IaC).
• Knowledge of cloud data warehousing solutions such as Snowflake and Fabric.
• Experience with Agile and DevOps methodologies and delivering business value through team collaboration.

Preferred Qualifications:

• Ability to influence and build consensus with diverse audiences; confident public speaker.
• Strong communication skills for conveying complex ideas concisely; proficiency with diagramming and presentation software.
• Experience in teaching or mentoring professionals.

Additional Information:

Learn more about SC&E: http://www.wwt.com/consulting-services-careers

Benefits include health and wellbeing programs, financial perks, paid time off, and additional perks like legal and pet insurance.

#LI-WWTACRIDER #LI-Remote

MLOps Engineer

Why WWT?

WWT fosters a collaborative environment to innovate and deliver cutting-edge solutions, with a strong culture and benefits. Founded in 1990, employing over 10,000 worldwide, and recognized repeatedly as a top workplace.

What is the Solutions Consulting & Engineering (SC&E) Team?

An organization focused on customer solutions, bringing together business and technical expertise to solve complex challenges.

Responsibilities:

• Develop, deploy, and operationalize scalable AI & ML solutions.
• Follow best practices in software architecture and design.
• Design and build feature engineering pipelines in collaboration with Data Engineering.
• Stay updated on new ML frameworks, data structures, and libraries.
• Mentor data scientists and engineers on software development best practices.

Work in cross-functional agile teams to innovate AI and MLOps solutions, advocating for scalable and maintainable analytics solutions, and providing expert consultation on complex technical topics.