AI/ML Engineer III

AI/ML Engineer III

Technergetics — Utica/Rome, NY area

A Note About Our AI-Assisted Interview Process

We use an AI application, “Alex Taylor,” to conduct first-round interviews for this position. The interview takes approximately 35 minutes. If we would like to interview you, you will receive an email invitation from “Alex” within ten business days of your application.

Alex is available 24/7, which lets us conduct far more first-round interviews than our human staff’s schedule alone would allow. Technergetics HR (and additional staff, as applicable) reviews every first-round interview. AI supports our decision-making, but all decisions about who advances to a first or second interview are made by our human staff. Candidates selected for a second-round interview will meet with the HR director and hiring manager.

Any data collected during the interview process, including AI-generated insights, is handled with care and confidentiality, in compliance with applicable data protection laws. Your responses are processed only to provide feedback on your skills and knowledge. Data is stored securely and will not be shared with third parties without your consent.

We understand some candidates may be hesitant to interview with an AI application — it is by no means perfect at this time. But as a company dedicated to research and development in AI/ML and other technologies, we see this as a chance to practice what we preach.

Opportunity Overview

Technergetics is looking for an AI/ML Engineer III to design, develop, and deploy advanced AI capabilities alongside a high-performing team of full-stack developers. This role centers on building production systems around foundation models, including agentic workflows, retrieval-augmented generation, and multimodal machine learning, for demanding government and commercial customers.

Contingent Position: This position is contingent upon contract award and funding.

Position Details

Salary Range: $125,000–$175,000 annually. The final offer depends on how many position qualifications the candidate meets, as well as education and experience. This is a full-time, exempt position.

Location, Travel, and Remote Work

• Candidates who are located within, or relocate to, a commutable distance of the Utica/Rome area can expect to be onsite 20% of their workweek, for access to company and AFRL (Air Force Research Lab) facilities, secure data, and customers. A relocation signing bonus may be available.
• Remote candidates outside a commutable distance to Utica/Rome will still be considered but may need to travel to the Utica/Rome area quarterly or more often, depending on company and client needs.
• This position also involves approximately 5%–10% travel to customer and client sites outside the Utica-Rome, NY area.

Due to the security clearance required for this position, only U.S. citizens are eligible to apply, per Executive Order 12968 (Access to Classified Information).

Responsibilities and Duties

The successful candidate will work on one or more of our Machine Learning (ML) software products, with day-to-day activities that include:

• Leading the design, development, and deployment of multi-modal machine learning architectures, including models and algorithms, to solve complex mission and business problems
• Designing and building agentic systems on top of large language models for operational deployment
• Implementing retrieval-augmented generation pipelines that ground model outputs against authoritative data sources
• Defining and running evaluation for model and agent behavior in production
• Optimizing model inference for production and edge/DDIL (denied, degraded, intermittent, and limited bandwidth) deployment scenarios
• Applying AI assurance practices and documenting model limitations to support accreditation and customer review
• Integrating state-of-the-art machine learning libraries, foundation models, and agent frameworks into existing software applications
• Developing and maintaining data pipelines and supporting software for collecting, preprocessing, and transforming data for machine learning tasks
• Designing software solutions, algorithms, and cloud architectures needed to satisfy product features and functionality defined by the product owner and other stakeholders in a production environment
• Leading, coaching, and mentoring junior data scientists, engineers, and other staff
• Contributing to phases of the software deve…