Machine Learning Engineer

About the role

The ideal candidate will have hands-on experience building and supporting Agentic AI solutions, integrating Large Language Models (LLMs), and developing scalable AI workflows in cloud environments. This position is focused on the practical implementation, optimization, and operationalization of AI agents in production environments rather than traditional machine learning model development. The engineer will be assigned business use cases and will own the design, implementation, and continuous improvement of AI-driven solutions that enhance decision-making and workflow efficiency across multiple business domains.

Responsibilities

• Design, develop, and optimize AI agents that support enterprise business workflows.
• Build and maintain agentic workflows that drive automation, execution, and business insights.
• Integrate LLMs and AI services into production environments.
• Utilize APIs and AI SDKs to enhance and extend AI agent capabilities.
• Develop backend services and integrations using Python.
• Support AI workloads leveraging GCP technologies and BigQuery.
• Optimize AI agent performance, token utilization, and cost efficiency.
• Partner with business stakeholders to understand and solve real-world use cases.
• Build scalable and maintainable AI solutions that improve decision-making across multiple business domains.
• Support deployment, monitoring, and operational excellence of AI-powered systems.

Requirements

• Strong Python development experience.
• Experience building or supporting AI Agents and Agentic Workflows.
• Experience working with LLMs and Generative AI technologies.
• Exposure to AI SDKs such as OpenAI, Anthropic, or similar platforms.
• Experience integrating APIs into AI-driven solutions.
• GCP cloud experience, including BigQuery and cloud-native services.
• Experience working with unstructured data.
• Understanding of AI agent optimization, deployment, and operational performance.
• Hands-on experience with agent orchestration frameworks such as LangChain, LangGraph, or Google Agent Development Kit (ADK).

Qualifications

• Background in AI Engineering, Software Engineering, Machine Learning Engineering, or Data Engineering.
• Experience deploying containerized applications using Docker.
• Exposure to CI/CD processes and automation pipelines.
• Experience working in multi-cloud environments (GCP preferred, Azure exposure helpful).
• Retail, supply chain, planning, forecasting, or allocation experience is a plus.
• SQL and/or R experience.

Benefits

Everforth Apex offers a range of supplemental benefits, including medical, dental, vision, life, disability, and other insurance plans that offer an optional layer of financial protection. We offer an ESPP (employee stock purchase program) and a 401K program which allows you to contribute typically within 30 days of starting, with a company match after 12 months of tenure. Everforth Apex also offers a HSA (Health Savings Account on the HDHP plan), a SupportLinc Employee Assistance Program (EAP) with up to 8 free counseling sessions, a corporate discount savings program and other discounts. In terms of professional development, Everforth Apex hosts an on-demand training program, provides access to certification prep and a library of technical and leadership courses/books/seminars once you have 6+ months of tenure, and certification discounts and other perks to associations that include CompTIA and IIBA. Everforth Apex has a dedicated customer service team for our Consultants that can address questions around benefits and other resources, as well as a certified Career Coach. You can access a full list of our benefits, programs, support teams and resources within our ‘Welcome Packet’ as well, which an Everforth Apex team member can provide.