1

Machine Learning Engineer Jobs in Utica, NY (NOW HIRING)

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

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

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

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

AI/ML Engineer Rome, NY 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 ...

Summary The AI Engineer is part of a highly collaborative team that develops cutting-edge machine ... Develops Artificial Intelligence and Machine Learning solutions to solve business problems and ...

Summary The AI Engineer is part of a highly collaborative team that develops cutting-edge machine ... Develops Artificial Intelligence and Machine Learning solutions to solve business problems and ...

Summary The AI Engineer is part of a highly collaborative team that develops cutting-edge machine ... Develops Artificial Intelligence and Machine Learning solutions to solve business problems and ...

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 ...

Data Engineer

Annsville, NY

$118K - $142K/yr

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 ...

The Principal AI Security Engineer leads and partners throughout the organization to build ... Designs and implement secure machine learning operations (MLOps) controls for datasets, features ...

The Principal AI Security Engineer leads and partners throughout the organization to build ... Designs and implement secure machine learning operations (MLOps) controls for datasets, features ...

The Principal AI Security Engineer leads and partners throughout the organization to build ... Designs and implement secure machine learning operations (MLOps) controls for datasets, features ...

Booz Allen is the leading provider of AI services to the nation-we're looking for a software engineer like you to create artificial intelligence and machine learning solutions that help solve The ...

Booz Allen is the leading provider of AI services to the nation-we're looking for a software engineer like you to create artificial intelligence and machine learning solutions that help solve The ...

AI/ML Software Engineer

Rome, NY · On-site

$86K - $198K/yr

Booz Allen is the leading provider of AI services to the nation-we're looking for a software engineer like you to create artificial intelligence and machine learning solutions that help solve The ...

AI/ML Software Engineer

Rome, NY · On-site

$86K - $198K/yr

Booz Allen is the leading provider of AI services to the nation-we're looking for a software engineer like you to create artificial intelligence and machine learning solutions that help solve The ...

Front End Developer

Utica, NY

$106K - $123K/yr

Hi Front End Developer Utica, NY 12+ Months - Frontend Developer We are seeking a skilled Frontend ... Foundational knowledge of machine learning algorithms, deep learning frameworks, and data analysis ...

next page

Showing results 1-20

Machine Learning Engineer information

See Utica, NY salary details

$32.2K

$131.6K

$197.7K

How much do machine learning engineer jobs pay per year?

As of Jun 16, 2026, the average yearly pay for machine learning engineer in Utica, NY is $131,553.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,700.00 and $158,400.00 per year, depending on experience, location, and employer.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What cities near Utica, NY are hiring for Machine Learning Engineer jobs? Cities near Utica, NY with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Utica, NY as of June 2026, with employment types broken down into 98% Full Time, and 2% Part Time. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $131,553 per year, or $63.2 per hour.
AI/ML Engineer

AI/ML Engineer

Raft

Rome, NY • On-site

Other

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

This is a U.S. based position. All of the programs we support require U.S. citizenship to be eligible for employment. All work must be conducted within the continental U.S.

Who we are:

Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.

Our flagship AI platform, [R]AIMS (Raft AI Mission System), enables operators and engineers to rapidly build, deploy, evaluate, and govern AI-powered mission workflows across highly dynamic operational environments. We are expanding our AI/ML presence in Rome, NY to support our customers and are looking for a hands-on AI/ML Engineer to contribute directly to model development, evaluation, and operational AI delivery.

About the role:

As an AI/ML Engineer embedded in Rome, NY, you will work directly on model development efforts while leveraging and extending [R]AIMS platform capabilities to accelerate experimentation, evaluation, deployment, and operational transition. This is a highly hands-on role for an engineer who wants to build real-world AI systems with direct mission impact.

You will work closely with platform engineers, AI leadership, and mission stakeholders to move models from experimentation through production. The work sits at the intersection of applied machine learning, model training and evaluation, AI platform engineering, and operational AI deployment. You will need to be comfortable operating across that full span: writing training pipelines one day, integrating a model into a containerized deployment the next, and briefing a technical stakeholder on evaluation results the day after that.

What You'll Do:
  • Build and evaluate machine learning models for mission-relevant use cases working directly with government researchers and program stakeholders to understand requirements and translate them into executable technical solutions
  • Develop and maintain model training, fine-tuning, and benchmarking workflows that are reproducible, well-documented, and usable by teammates without hand-holding
  • Build and improve evaluation pipelines for repeatable, rigorous performance measurement across model architectures, datasets, and operational scenarios
  • Integrate models into production-ready [R]AIMS platform infrastructure, working with platform engineers to ensure deployments are containerized, observable, and operationally sustainable
  • Support experimentation across model architectures and datasets, maintaining clear records of results and surfacing actionable findings to AI leadership and mission stakeholders

What we are looking for:

  • 3 to 6 years of hands-on experience building and shipping production software or AI/ML systems
  • Strong Python software engineering skills; writes clean, maintainable, production-quality code rather than notebook-only scripts
  • Demonstrated experience developing and evaluating machine learning models, with a clear understanding of what makes an evaluation rigorous versus misleading
  • Hands-on familiarity with modern ML frameworks such as PyTorch, TensorFlow, JAX, or Hugging Face
  • Experience building and managing model training pipelines and experimentation workflows at a level beyond tutorial projects
  • Experience working with distributed systems or cloud-native environments; comfortable in infrastructure that isn't fully managed for you
  • Strong debugging instincts; able to diagnose failure modes in complex pipelines and explain findings clearly to both technical and non-technical audiences
  • Ability to work independently and manage workstreams without close supervision while staying well-integrated with a distributed team
  • Strong written and verbal communication skills; able to produce clear technical documentation, status updates, and evaluation summaries
  • Ability to obtain Security+ certification within the first 90 days of employment
  • S. citizenship required; ability to obtain and maintain a Top Secret/SCI clearance
Highly Preferred:
  • Experience fine-tuning foundation models, LLMs, or multimodal models for specific domain tasks or constrained operational environments
  • Experience designing or operating model evaluation frameworks and benchmarking pipelines at scale
  • Experience with Kubernetes and containerized ML workloads, including deploying and debugging GPU-enabled inference services
  • Experience with distributed training or large-scale inference systems
  • Familiarity with streaming or event-driven architectures such as Kafka or Flink, particularly as they relate to real-time model inputs or outputs
  • Experience building secure, compliant AI systems for regulated or mission-critical environments, including familiarity with RMF or IL requirements
  • Prior defense, national security, or government R&D experience, particularly with AFRL or Air Force programs
  • Experience working in prototype-to-production environments where research artifacts need to become operational systems
  • Active Secret or Top Secret clearance strongly preferred
What Success Looks Like
  • Models developed and evaluated at AFRL are delivered with clear, rigorous documentation of performance, limitations, and operational considerations-not handed off as black boxes
  • Evaluation pipelines are repeatable and trusted by the broader team; results are reproducible and traceable
  • Model integrations into [R]AIMS are clean, containerized, and maintainable by platform engineers without needing the original model developer in the loop
  • AFRL stakeholders view Raft as a technically credible, reliable partner; your presence in Rome strengthens that relationship over time
  • The gap between experimentation and operational deployment shortens with each program cycle because of the infrastructure and workflows you helped build

Clearance Requirements:

  • No clearance required to start
  • Must be eligible for and willing to obtain a Top Secret/SCI clearance; active clearance strongly preferred

Salary Range: $170,000.00 - $220,000.00

Work Type:

  • Hybrid in Rome, NY; candidates must be based in or willing to relocate to the Rome, NY area to support a hybrid schedule
  • Up to 25% travel

What we will offer you:

  • Highly competitive salary
  • Fully covered healthcare, dental, and vision coverage
  • 401(k) and company match
  • Take as you need PTO + 11 paid holidays
  • Education & training benefits
  • Generous Referral Bonuses
  • And More!

Our Vision Statement:

We bridge the gap between humans and data through radical transparency and our obsession withthemission.

Our Customer Obsession:

We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.

How do we get there?

Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking,and collaboration is a norm.

Raft's core philosophy isUbuntu: IAm, BecauseWe are. We support our"nadi"by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration.

We're an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.