AI/ML Engineer III

Technergetics

AI/ML Engineer III building production multimodal, agentic, and retrieval-augmented AI systems for Technergetics. Supporting government and commercial R&D customers through deployment, evaluation, and AI assurance.

Posted 8/20/2026full-timeUtica • New York • 🇺🇸 United StatesMid-LevelSenior💰 $125,000 - $175,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying advanced multimodal machine learning architectures and models, with a strong focus on large language models and AI assurance practices. Proficient in leading technical teams and collaborating across functions to deliver innovative ML solutions in production environments.

Highest-signal resume keywords

Machine Learning Systems EngineeringLarge Language Model DevelopmentPython ProgrammingCloud Platforms (AWS, Azure, Google Cloud)AI Assurance Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningMultimodal ModelsModel Inference OptimizationRetrieval-Augmented GenerationAutomated Testing (pytest)Fine-Tuning and DistillationAPI DevelopmentData Pipeline DevelopmentAsynchronous ProgrammingModel Evaluation and Benchmarking

Soft Skills

LeadershipCommunicationTeamworkMentoringCollaboration

Tools & Technologies

KubernetesDockerLinuxGitLab PipelinesHugging Face Ecosystem

Certifications & Qualifications

Top Secret Security Clearance

Industry Keywords

AI SafetyDevSecOpsAgile Software DevelopmentCross-Modal EmbeddingPrompt Engineering

Tech Stack

Tools & technologies

AWSAzureCloudDockerKubernetesLinuxPythonPyTorchSDLC

About the role

Key responsibilities & impact

Design, develop, and deploy advanced multimodal machine learning architectures, models, and algorithms
Design and build agentic systems on top of large language models for operational deployment
Implement retrieval-augmented generation pipelines grounded in authoritative data sources
Define and run evaluation for model and agent behavior in production
Optimize model inference for production and edge/DDIL deployment scenarios
Apply AI assurance practices and document model limitations for accreditation and customer review
Integrate machine learning libraries, foundation models, and agent frameworks into existing applications
Develop and maintain data pipelines and supporting software for collecting, preprocessing, and transforming ML data
Design software solutions, algorithms, and cloud architectures for product features in production
Lead, coach, and mentor junior data scientists, engineers, and staff
Contribute across the software development life cycle, including analysis, requirements, design, prototyping, coding, testing, deployment, migration, and support
Participate in daily scrums and organize and prioritize workload with the scrum team
Collaborate with cross-functional teams to translate business requirements into ML solutions
Perform unit testing and debugging and contribute to code reviews
Stay current on AI/ML approaches, frameworks, and industry trends
Serve as an AI subject matter expert on advanced R&D projects for government and commercial customers
Contribute to or lead proposal writing for new opportunities

Requirements

What you’ll need

Master’s degree from an accredited college or university in computer science, computer engineering, artificial intelligence, machine learning, or a closely related discipline; or a Bachelor’s degree in one of these fields combined with seven or more years of directly relevant professional experience in lieu of a Master’s degree
Minimum three years of professional experience in machine learning or AI systems engineering
At least one year building with large language models or other foundation models in a production setting
Strong proficiency in Python, including asynchronous programming and modern packaging and dependency management
Working knowledge of server-side development, API definitions, REST services, streaming, and asynchronous services
Fluency with Kubernetes or Docker, including GPU scheduling and resource management
Hands-on work with AWS, Azure, or Google Cloud
Comfort with Linux platforms and command-line environments
Familiarity with Continuous Delivery/Continuous Integration, DevSecOps, and GitLab Pipelines
Proficiency with automated testing in Python using pytest
Ability to train and deploy machine learning models with PyTorch and the Hugging Face ecosystem
Experience building applications on large language models, including prompt engineering, structured output, and context management
Fluency with agentic frameworks and patterns, including multi-step tool use, planning, memory, state management, and Model Context Protocol
Practical command of retrieval-augmented generation, embeddings, vector databases, and hybrid or re-ranked retrieval
Ability to design and run LLM evaluation, benchmarks, golden datasets, LLM-as-judge methods, tracing, and observability tooling
Command of fine-tuning, LoRA/PEFT, quantization, and distillation
Ability to serve models in production with inference frameworks and deploy to edge or resource-constrained environments
Grounding in AI safety and assurance practices, including guardrails, filtering, prompt injection mitigation, and human-in-the-loop design
Direct work with multimodal models and cross-modal embedding
Demonstrated leadership on technical tasks and/or technical teams, Agile software development, and leading tasks to completion
Excellent communication and teamwork skills
Only U.S. citizens are eligible to apply due to the required security clearance
Must meet and maintain eligibility for, at minimum, Top Secret access to classified information
Ph.D. in a relevant field is strongly preferred

Benefits

Comp & perks

Health insurance
Life insurance
Disability insurance
Dental insurance
Vision insurance
401(k) plan with a 3% company contribution and 3% company match
Generous Paid Time Off, including a PTO “gift day” for your birthday
11 federal holidays per year
Three weeks of paid maternity/paternity leave
Annual technology allowance
Referral bonuses
Professional recognition awards
Healthcare stipends
Tuition/education reimbursement once eligibility requirements are met
Flexible daily start and stop times for most projects and positions
Relocation signing bonus may be available