AI / ML Engineer [Remote]

This position is posted by Jobgether on behalf of a partner company. We are currently looking for an AI / ML Engineer in the United States.

This role sits at the intersection of machine learning engineering, AI systems design, and large-scale data-driven decision-making, focused on solving complex challenges in the energy and utility sector. You will contribute to the development of advanced AI and ML solutions that combine predictive modeling, optimization, and generative AI to support critical infrastructure and sustainability goals. Working closely with data scientists and software engineers, you will help design, build, and deploy scalable machine learning systems that power real-world applications. The environment is highly collaborative and innovation-driven, with a strong emphasis on applied AI, production readiness, and measurable impact. You will work across diverse use cases including forecasting, geospatial analysis, and intelligent decision systems. This is a high-impact role where your work directly supports the modernization and efficiency of energy systems.

Accountabilities:

• Collaborate with cross-functional teams to design, develop, and deploy scalable AI and machine learning solutions integrated into production systems.
• Build reusable Python libraries and engineering components to support ML pipelines, data processing workflows, and AI system development.
• Contribute to the design and implementation of modern AI architectures, including RAG systems, LLM integrations, and agent-based workflows.
• Develop frameworks for evaluating and monitoring AI systems, including reasoning quality, consistency, performance, and fairness.
• Support database design and optimization, including writing efficient queries for large-scale data processing and retrieval.
• Translate complex machine learning and AI requirements into structured technical tasks and actionable development plans.
• Ensure robust testing practices and participate in code reviews to maintain high-quality, production-ready ML systems.
• Stay current with advancements in machine learning engineering, generative AI, and AI orchestration, integrating best practices into workflows.
• Contribute to Agile development and continuous delivery processes across AI and data engineering teams.

Requirements:

• Master’s degree in Computer Science, Data Science, Software Engineering, or related field (PhD preferred).
• 7+ years of experience building, deploying, and maintaining machine learning systems in production environments.
• Strong proficiency in Python, including experience building reusable packages and scalable data pipelines.
• Hands-on experience with cloud platforms such as AWS, Azure, or GCP, including CI/CD and containerized deployments.
• Solid understanding of ML system design, MLOps principles, and end-to-end model lifecycle management.
• Experience with distributed computing frameworks and relational/non-relational databases.
• Familiarity with Databricks and large-scale data processing environments.
• Experience working with generative AI frameworks such as LangChain, LangGraph, LlamaIndex, Hugging Face, or AutoGen.
• Exposure to agentic AI systems, AI orchestration, or LLM-based decision workflows is highly desirable.
• Strong analytical and problem-solving skills with the ability to decompose complex AI problems into actionable engineering tasks.
• Excellent communication and collaboration skills in cross-functional environments.
• Nice to have: experience in the utility, energy, or power sector and strong Databricks expertise.

Benefits:

• Competitive salary range of $115,000–$145,000 USD plus annual bonus.
• Comprehensive medical, dental, vision, and disability insurance coverage.
• Company-paid life insurance and additional wellness protections.
• Flexible time off policy supporting work-life balance.
• 401(k)/RRSP retirement plan with employer matching.
• Fully remote work environment with minimal travel requirements.
• Opportunity to work on high-impact AI systems supporting energy transition and sustainability.
• Collaborative, knowledge-driven culture focused on innovation and continuous learning.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.