AI / ML Engineer at Jobgether

, , United States -

Full Time

Start Date

Immediate

Expiry Date

05 Sep, 26

Salary

0.0

Posted On

07 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Machine Learning Engineering, Generative AI, MLOps, System Design, Cloud Platforms, CI/CD, RAG Pipelines, LLM Integration, Distributed Computing, Data Pipelines, LangChain, LangGraph, Hugging Face, Database Design, Predictive Analytics

Industry

Internet Marketplace Platforms

Description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a AI / ML Engineer based in United States. This role sits at the intersection of machine learning, software engineering, and real-world energy systems, focusing on building intelligent tools that help utilities navigate complex operational and sustainability challenges. You will contribute to the design and deployment of next-generation AI systems, including predictive models, generative AI workflows, and agent-based architectures. The work spans diverse problem domains such as forecasting, grid optimization, geospatial intelligence, and decision automation. You will collaborate closely with data scientists and engineers to turn advanced ML research into scalable production systems. This is a highly applied engineering role where experimentation, system design, and production reliability all converge. Your work will directly support utilities in improving efficiency, reliability, and long-term sustainability outcomes. \n Accountabilities: Design, build, and deploy scalable AI and machine learning systems that support predictive analytics, optimization, and generative AI use cases in production environments. Develop reusable Python libraries, data pipelines, and modular components to support ML workflows and accelerate engineering productivity. Contribute to the design and implementation of AI system architectures, including RAG pipelines, LLM integrations, and agent-based workflows. Build evaluation, monitoring, and testing frameworks for ML and AI systems, focusing on performance, reliability, consistency, and fairness. Collaborate with cross-functional teams to translate complex business and technical requirements into actionable ML and software solutions. Optimize data storage, retrieval, and processing through effective database design and query performance improvements. Stay current with advances in machine learning, generative AI, and MLOps, integrating relevant innovations into production systems. Requirements: 7+ years of professional experience in machine learning engineering, software engineering, or data science roles focused on building production-grade ML systems. Advanced degree in Computer Science, Software Engineering, Data Science, or a related field (Master’s preferred, PhD a plus). Strong proficiency in Python and experience building reusable packages, automation tools, and production ML pipelines. Deep understanding of ML system design, including model lifecycle management, MLOps practices, and scalable inference architectures. Hands-on experience with cloud platforms such as AWS, Azure, or GCP, along with containerization and CI/CD workflows. Familiarity with distributed computing frameworks, relational and non-relational databases, and large-scale data processing systems. Experience with generative AI frameworks such as LangChain, LangGraph, Hugging Face, or similar tooling for LLM-based applications. Strong analytical and problem-solving skills with the ability to decompose complex systems into practical engineering tasks. Excellent collaboration and communication skills, with experience working in cross-functional, product-oriented environments. Exposure to energy, utilities, or infrastructure domains is a strong plus. Benefits: Competitive compensation package with annual bonus eligibility Comprehensive medical, dental, and vision insurance coverage Company-paid life insurance, as well as short-term and long-term disability coverage Flexible time off policy supporting work-life balance Retirement savings plan with employer matching (401k/RRSP depending on location) Flexible spending accounts for medical and dependent care expenses Fully remote work environment with minimal travel requirements Paid parental leave and family support benefits Opportunities for continuous learning and professional development in AI and ML \n 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! Why Apply Through Jobgether? 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. #LI-CL1

Responsibilities

Design and deploy scalable AI/ML systems, including predictive models and generative AI workflows, to solve energy sector challenges. Develop reusable Python libraries and monitoring frameworks to ensure the reliability and performance of production-grade AI architectures.