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Senior Machine Learning Engineer Jobs in Rome, NY

AI/ML Engineer III

Rome, NY ยท On-site +1

$125K - $175K/yr

AI/ML Engineer III Technergetics -- Utica/Rome, NY area A Note About Our AI-Assisted Interview ... Integrating state-of-the-art machine learning libraries, foundation models, and agent frameworks ...

New

AI/ML Engineer III

Utica, NY ยท On-site +1

$125K - $175K/yr

AI/ML Engineer III Technergetics -- Utica/Rome, NY area A Note About Our AI-Assisted Interview ... Integrating state-of-the-art machine learning libraries, foundation models, and agent frameworks ...

New

AI/ML Engineer III

Utica, NY ยท On-site +1

$125K - $175K/yr

AI/ML Engineer III Technergetics - Utica/Rome, NY area A Note About Our AI-Assisted Interview ... Integrating state-of-the-art machine learning libraries, foundation models, and agent frameworks ...

Engineer

Rome, NY ยท On-site

As an Engineer embedded in Rome, NY, you will work directly on model development efforts while ... Build and evaluate machine learning models for mission-relevant use cases working directly with ...

Engineer

Rome, NY ยท On-site

As an Engineer embedded in Rome, NY, you will work directly on model development efforts while ... Build and evaluate machine learning models for mission-relevant use cases working directly with ...

Engineer

Rome, NY ยท On-site

As an Engineer embedded in Rome, NY, you will work directly on model development efforts while ... Build and evaluate machine learning models for mission-relevant use cases working directly with ...

Engineer

Rome, NY ยท On-site

As an Engineer embedded in Rome, NY, you will work directly on model development efforts while ... Build and evaluate machine learning models for mission-relevant use cases working directly with ...

Engineer Rome, NY Apply This is a U.S. based position. All of the programs we support require U.S ... Build and evaluate machine learning models for mission-relevant use cases working directly with ...

Support senior engineers in designing photonic circuits that support quantum algorithms and ... machine learning and artificial intelligence, AI-enabled edge devices, and many more. Beware of ...

New

Senior Software Product Manager

East Syracuse, NY ยท On-site

$119K - $157K/yr

... by AI and machine learning. * Define and track product KPIs tied to customer outcomes (yield ... Spend significant time with process engineers, equipment engineers, integration engineers, and fab ...

Senior Software Product Manager

East Syracuse, NY ยท On-site

$119K - $157K/yr

... by AI and machine learning. * Define and track product KPIs tied to customer outcomes (yield ... Spend significant time with process engineers, equipment engineers, integration engineers, and fab ...

Senior Software Product Manager

East Syracuse, NY ยท On-site

$119K - $157K/yr

... by AI and machine learning. * Define and track product KPIs tied to customer outcomes (yield ... Spend significant time with process engineers, equipment engineers, integration engineers, and fab ...

This role is part of a multidisciplinary team integrating advanced analytics, machine learning, and engineering practices into mission-critical environments at Combatant Commands. You will help shape ...

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Showing results 1-20

Senior Machine Learning Engineer information

See Rome, NY salary details

$56.3K

$119.8K

$173.7K

How much do senior machine learning engineer jobs pay per year?

As of Aug 25, 2026, the average yearly pay for senior machine learning engineer in Rome, NY is $119,825.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,900.00 and $135,900.00 per year, depending on experience, location, and employer.

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What are the key skills and qualifications needed to thrive as a senior machine learning engineer, and why are they important?

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

What is the difference between Senior Machine Learning Engineer vs Data Scientist?

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What cities near Rome, NY are hiring for Senior Machine Learning Engineer jobs?

Cities near Rome, NY with the most Senior Machine Learning Engineer job openings:

Infographic showing various Senior Machine Learning Engineer job openings in Rome, NY as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 22% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $119,825 per year, or $57.6 per hour.

AI/ML Engineer III

Rome, NY โ€ข On-site, Remote

$125K - $175K/yr

Full-time

Posted 3 days ago

New


Job description

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 development life cycle, including functional analysis, technical requirements, technical design, prototyping, coding, testing, deployment, data migration, and support
  • Participating in daily scrums and working with the scrum master and scrum team to organize and prioritize workload through story-pointing, supporting delivery timelines and priorities
  • Collaborating with cross-functional teams to understand business requirements and translate them into machine learning solutions
  • Performing unit testing and debugging to identify and fix software defects, and contributing to code reviews with constructive feedback to peers
  • Staying current on new AI/ML approaches, frameworks, and industry trends
  • Serving as an AI subject matter expert for small teams of researchers and engineers on advanced R&D projects funded by government and/or commercial customers, and contributing to or leading proposal writing for new opportunities within your area of expertise
Education and Certifications

This position generally requires a Master's degree from an accredited college or university in computer science, computer engineering, artificial intelligence, machine learning, or a closely related discipline. A Ph.D. in one of these fields is strongly preferred. A Bachelor's degree in one of these fields, combined with seven or more years of directly relevant professional experience, will be considered in lieu of a Master's degree.

QualificationsExperience and Foundational Engineering
  • At minimum, three years of professional experience in machine learning or AI systems engineering, including 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, etc.)
  • Fluency with containerization and deployment frameworks such as Kubernetes or Docker, including GPU scheduling and resource management for training and inference workloads
  • Hands-on work with at least one major cloud platform (AWS, Azure, or Google Cloud)
  • Comfort with Linux platforms and command-line environments
  • Familiarity with Continuous Delivery/Continuous Integration (DevSecOps, GitLab Pipelines, etc.)
  • Proficiency with automated testing in Python (pytest), including regression suites for non-deterministic model and agent behavior
Artificial Intelligence and Machine Learning
  • Demonstrated ability to train and deploy machine learning models with PyTorch and the Hugging Face ecosystem (transformers, datasets, accelerate)
  • A track record of building applications on top of large language models, including prompt engineering, structured output, and context management
  • Fluency with agentic frameworks and patterns such as LangGraph, LangChain, CrewAI, AutoGen, Pydantic AI, or vendor agent SDKs, including multi-step tool use, planning, memory, and state management, and with integrating models, tools, and data sources through open standards such as Model Context Protocol (MCP)
  • Practical command of retrieval-augmented generation, including chunking and embedding strategy, vector databases (pgvector, Milvus, Qdrant, Weaviate, FAISS), and hybrid or re-ranked retrieval
  • Ability to design and run LLM evaluation, including task-specific benchmarks, golden datasets, LLM-as-judge methods, and tracing and observability tooling (LangSmith, Langfuse, Arize, Weights & Biases)
  • Command of model adaptation techniques including fine-tuning, LoRA/PEFT, quantization, and distillation, and the judgment to know when adaptation is preferable to prompting or retrieval
  • Proven ability to serve models in production with inference frameworks such as vLLM, TensorRT-LLM, Triton Inference Server, Ollama, or ONNX Runtime, including latency, throughput, and cost tradeoffs, as well as deployment to edge or resource-constrained environments, including on-device inference
  • Grounding in AI safety and assurance practices, including guardrails, input and output filtering, prompt injection mitigation, and human-in-the-loop design
  • Direct work with multimodal models and cross-modal embedding across text, imagery, video, audio, or geospatial data
Leadership and Collaboration
  • Demonstrated leadership on technical tasks and/or technical teams, including Agile software development and leading one or more tasks to completion
  • Excellent communication and teamwork skills, including the ability to explain technical tradeoffs to non-technical stakeholders and customers
Nice to Have
  • Exposure to DoD cloud and software factory environments such as Platform One, BESPIN, AF Cloud One, DAF CLOUDworks, or AWS GovCloud, and with ATO and RMF processes at IL4/IL5
  • Familiarity with DoD and federal AI policy and governance, including CDAO Responsible AI guidance
  • Work with distributed training frameworks and schedulers (DeepSpeed, FSDP, Ray, Slurm)
  • Knowledge of knowledge graphs, ontologies, or Resource Description Framework (RDF), particularly as applied to graph-based retrieval (GraphRAG) and grounding
  • Background in developing modern full-stack web applications with frameworks such as Node, React, React Native, or Django
  • Basic working knowledge of Go, Java, C++, or other compiled languages
  • Contributions to open source AI/ML projects, or published applied AI research
Clearance

Selected applicants will undergo a security investigation and must meet and maintain eligibility for, at minimum, Top Secret access to classified information.

Benefits

Our benefits package includes health, life, disability, dental, and vision insurance, plus a 401(k) plan with a 3% company contribution and 3% company match.

Additional perks include:

  • 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 and professional recognition awards
  • Healthcare stipends
  • Tuition/education reimbursement (once eligibility requirements are met)
  • Flexible daily start and stop times for most projects and positions
Company Description

Technergetics is a U.S.-based company headquartered in Utica, NY, with employees and clients located throughout the country. The Utica/Rome area is a hub of cutting-edge cyber technology research, bolstered by the Griffiss Business & Technology Park's tenants and facilities, including the Air Force Research Lab (AFRL). At Technergetics, we work with a wide variety of technologies, including mobile and web apps, quantum computing, machine learning and artificial intelligence, AI-enabled edge devices, and more.

⚠ Beware of Fraudulent Job Offers and Postings

Technergetics will never extend an offer of employment without a thorough interview process that includes a face-to-face interview — either in person or via a virtual Teams meeting — from an official Technergetics email address (@techngs.com). If you receive correspondence from any other email address, it is a scam.

Technergetics does not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.