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Machine Learning Engineer Jobs in Manchester, NH

DEKA

Machine Learning Engineer

Manchester, NH · On-site

We're looking for a Machine Learning Engineer who can operate at the intersection of backend engineering and applied machine learning. If you want to design distributed systems, deploy production ML ...

Bespoke Labs

Machine Learning Engineer

Nashua, NH · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Manchester, NH · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Concord, NH · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Derry, NH · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Rockstar Games

Senior Machine Learning Engineer

Andover, MA

$105K - $145K/yr

Rockstar Games is on the lookout for a skilled Senior Machine Learning Engineer with strong software development skills who is passionate about games, big data and Machine Learning to join a team ...

GBG

Senior Machine Learning Engineer (3968)

Manchester, NH · On-site

$104K - $142K/yr

Senior Machine Learning Engineer The Senior Machine Learning Engineer is a senior individual contributor responsible for designing, developing, deploying, and continuously improving machine learning ...

GBG

Senior Machine Learning Engineer (3968)

Manchester, NH

$104K - $142K/yr

Senior Machine Learning Engineer The Senior Machine Learning Engineer is a senior individual contributor responsible for designing, developing, deploying, and continuously improving machine learning ...

GBG

Senior Machine Learning Engineer (3968)

Manchester, NH · On-site

$104K - $142K/yr

Senior Machine Learning Engineer The Senior Machine Learning Engineer is a senior individual contributor responsible for designing, developing, deploying, and continuously improving machine learning ...

Rockstar Games

Senior Machine Learning Engineer

Andover, MA · On-site

$124K - $163K/yr

Rockstar Games is on the lookout for a skilled Senior Machine Learning Engineer with strong software development skills who is passionate about games, big data and Machine Learning to join a team ...

Rockstar Games

Senior Machine Learning Engineer

Andover, MA · On-site

$105K - $145K/yr

They are seeking a Senior Machine Learning Engineer to join their Analytics team, focusing on building data science products that enhance game design and player engagement. Responsibilities : • ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Manchester, NH

Machine Learning Engineer information

See Manchester, NH salary details

$31.4K

$128.2K

$192.7K

How much do machine learning engineer jobs pay per year?

As of Jun 27, 2026, the average yearly pay for machine learning engineer in Manchester, NH is $128,220.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,100.00 and $154,300.00 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.

More about Machine Learning Engineer jobs
What are popular job titles related to Machine Learning Engineer jobs in Manchester, NH? For Machine Learning Engineer jobs in Manchester, NH, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Manchester, NH look for? The top searched job categories for Machine Learning Engineer jobs in Manchester, NH are:
What cities near Manchester, NH are hiring for Machine Learning Engineer jobs? Cities near Manchester, NH with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Manchester, NH as of June 2026, with employment types broken down into 1% As Needed, 97% Full Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $128,220 per year, or $61.6 per hour.

Machine Learning Engineer

DEKA

Manchester, NH • On-site

Full-time

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

Job description

We're looking for a Machine Learning Engineer who can operate at the intersection of backend engineering and applied machine learning. If you want to design distributed systems, deploy production ML models, and architect scalable data pipelines that make a measurable difference - this is your opportunity, and it starts with the software you design and deliver at DEKA.
This role is on-site at DEKA in Manchester, NH. Relocation is not available, local candidates only.
How You Will Make an Impact:
  • Design and implement scalable backend services and microservices powering data-intensive, real-world applications
  • Build and deploy production ML models across the full lifecycle from feature engineering and training through evaluation, deployment, and monitoring
  • Develop and maintain event-driven distributed pipelines using Apache Kafka, Apache Spark, and related technologies
  • Architect systems that integrate ML models with rule-based decision engines for automated, real-time decisioning
  • Collaborate across disciplines to translate complex requirements into reliable, elegant engineering solutions
  • Contribute to AI/LLM-driven workflows and orchestration systems that push the boundaries of what software can do
Required Experience/Knowledge:
  • M.S. in Computer Science, AI, or a related field
  • 6+ years in backend software engineering and distributed systems
  • Strong proficiency in Java (Spring Boot, Spring MVC, Hibernate) and Python
  • Hands-on experience building and deploying production ML models (PyTorch or equivalent)
  • Experience with distributed systems and streaming technologies: Apache Kafka, Apache Spark, ZooKeeper
  • Solid understanding of microservices architecture, REST/SOAP APIs, and object-oriented design
  • Experience with relational and NoSQL databases (Oracle, IBM Db2, MSSQL, MongoDB)
  • Familiarity with AWS or equivalent cloud platforms
  • Strong problem-solving skills
  • Intrinsic drive to understand how things work and make them better
  • Excellent communicating and collaboration across engineering, data, and product teams
  • Strong attention to detail

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