Analytics & Artificial Intelligence Engineer

Analytics & Artificial Intelligence Engineer

Company Description

PEARCE SERVICES is a leading independent service provider of outsourced repair, maintenance, and engineering services to critical infrastructure in the renewable energy, power generation, and telecom industries. Pearce offers innovative, tech-enabled services for telecom, renewable energy, electric vehicle (EV), and energy storage system infrastructure customers. With over 2,000 team members nationwide, Pearce delivers comprehensive engineering, maintenance, repair, and repowering solutions, ensuring the seamless operation of the United States wireless and wireline telecom, commercial and utility-scale solar and wind projects, EV charging stations, as well as large-scale power generation and energy storage assets.

PEARCE SERVICES is seeking enthusiastic and talented AI/ML engineers who are committed to developing AI/ML solutions for increasing efficiency and delivering value to users. This role will require you to be well conversant with the latest developments in the AI/ML field and develop and deploy solutions for various optimization and data analytics tasks.

Key Responsibilities

• Collaborate with cross-functional teams including data engineering, product management, and business stakeholders to identify AI opportunities and deliver impactful solutions.
• Lead the design and implementation of scalable AI/ML models for predictive analytics, natural language processing, computer vision, optimization systems, LLM-powered copilots, intelligent assistants and agentic workflows.
• Develop and maintain reusable components, frameworks, and pipelines for model training, evaluation, and deployment.
• Optimize model performance and ensure robustness, fairness, and explainability in production environments.
• Conduct comprehensive LLM evaluation, including prompt testing, factuality validation, safety checks, and human-in-the-loop reviews.
• Contribute to the establishment of coding best practices, model governance, and responsible AI policies across the engineering team.
• Stay current with the latest research and trends in AI/ML and proactively introduce innovative approaches.
• Mentor junior engineers and contribute to the technical growth of the team.
• Ensure thorough documentation of model development processes, data analysis methodologies, and project outcomes.

Basic Qualifications

• Master’s degree or PhD in computer science, artificial intelligence, operational research, or related fields.
• 8+ years of experience in developing and deploying AI/ML solutions with 2+ years building generative AI based applications.
• Strong programming skills Python and TypeScript with experience in TensorFlow, PyTorch, OpenCV and HuggingFace libraries on Linux operating systems.
• Experience with vector databases and RAG implementation.
• Hands-on experience with MLOps and LLMOps tools and workflows (i.e. MLflow, Azure Machine Learning) for model versioning, monitoring, and rollback strategies.
• Experience with LLM evaluation techniques, such as grounded response testing, response scoring, safety filters, and user feedback loops.
• Strong software engineering skills, ability to build robust, scalable, maintainable and version-controlled software systems.
• Proficiency in CI/CD, MLOps and LLMOps on Azure cloud platform.
• Self-starter, ability to work independently, mentor junior engineers, and collaborate cross-functionally.
• Excellent communication skills, able to translate complex technical concepts to business stakeholders.
• Demonstrated ability to innovate and drive the adoption of new AI/ML techniques.
• Flexibility to collaborate with stakeholders in the US time zone.
• Willingness to work in night shift (5pm – 2am IST)

Preferred Qualifications

• Experience and domain expertise in predictive maintenance, field data capture, optimization modelling or geospatial intelligence.
• Experience in developing and deploying customized deep research agents on Microsoft platforms such as Azure Machine Learning, AI Foundry, Fabric, Copilot Studio and Teams.
• Experience in finetuning and rollout customized LLM on Azure or SLM on iOS.
• Experience in vision language models, multi-model vector databases and multi-model RAG implementation.
• Experience in multi-agent LLM pipelines using MCP or A2A and orchestration tools (Semantic Kernel, AutoGen, LangGraph, UIPath) to support complex agentic workflows.