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Machine Learning Engineer Jobs in Stamford, CT (NOW HIRING)

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a small group of technologists whose primary function is building the infrastructure that powers our ...

Machine Learning Engineer

New York, NY · On-site

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a small group of technologists whose primary function is building the infrastructure that powers our ...

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

Sr. Machine Learning Engineer Location: New York, NY Sponsorship: Yes Relocation: Yes Industry: Machine Learning A leading provider of AI is looking for a Sr. ML Engineer. Our client is an industry ...

Sr. Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

The Crown Is Yours As a Senior Machine Learning Engineer, you'll join a team of algorithm experts and data science technologists building innovative data products that solve analytically complex ...

Senior Machine Learning Engineer

New York, NY · On-site +1

$114K - $157K/yr

Position Overview As a Senior Machine Learning Engineer, you will play a key role in designing, developing, and evolving machine learning systems that support conversational AI, search, multi-agent ...

Machine Learning Engineer

New York, NY · On-site

$160K - $210K/yr

About the role We are seeking a Machine Learning Engineer to strengthen our element classification system - working closely with data scientists and data annotators to ship and improve entity ...

The Crown Is Yours As a Senior Machine Learning Engineer, you'll join a team of algorithm experts and data science technologists building innovative data products that solve analytically complex ...

About the Role Our Machine Learning Engineering team powers personalized experiences for hundreds of millions of customers across thousands of brands. As a Senior Machine Learning Engineer, you will ...

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

Senior Machine Learning Engineer, AI Research About the Role GEICO is redefining the insurance landscape throughcutting-edgeArtificial Intelligence, and the AI Research team is driving this ...

Machine Learning Engineer

New York, NY · On-site

$90K - $254K/yr

We are in search of an exceptional Machine Learning Engineer to join our accomplished team. In this role, you will take the lead in developing and fine-tuning predictive ML models, with a primary ...

Machine Learning Engineer

New York, NY · Hybrid

$90K - $254K/yr

We are in search of an exceptional Machine Learning Engineer to join our accomplished team. In this role, you will take the lead in developing and fine-tuning predictive ML models, with a primary ...

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Machine Learning Engineer information

See Stamford, CT salary details

$33.6K

$137.3K

$206.3K

How much do machine learning engineer jobs pay per year?

As of Jun 15, 2026, the average yearly pay for machine learning engineer in Stamford, CT is $137,303.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,200.00 and $165,300.00 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.

What are the most commonly searched types of Machine Learning Engineer jobs in Stamford, CT? The most popular types of Machine Learning Engineer jobs in Stamford, CT are:
What are popular job titles related to Machine Learning Engineer jobs in Stamford, CT? For Machine Learning Engineer jobs in Stamford, CT, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Stamford, CT look for? The top searched job categories for Machine Learning Engineer jobs in Stamford, CT are:
What cities near Stamford, CT are hiring for Machine Learning Engineer jobs? Cities near Stamford, CT with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Stamford, CT as of June 2026, with employment types broken down into 97% Full Time, 2% Part Time, and 1% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $137,303 per year, or $66 per hour.
Machine Learning Engineer

$200K - $300K/yr

Other

Posted 5 days ago


Job description

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a small group of technologists whose primary function is building the infrastructure that powers our quantitative researchers. This is a unique opportunity to work at the intersection of machine learning and systematic trading - building tools that directly determine how fast our researchers can move, and how effectively our GPU cluster translates into research output.

In this role, you will be responsible for the development of our ML research platform: the systems that manage data and compute, track experiments, and enable researchers to go from idea to result as efficiently as possible. You will work closely with quants and engineers alike and will play a central role in shaping how ML is done at the firm as we scale our capabilities. We mostly use Python, C++ and Java with a variety of open-source tools along with proprietary solutions.

THE ROLE

  • Design and build experiment tracking, job orchestration, and reproducibility infrastructure so researchers can iterate quickly, compare runs reliably, and recover from failures without losing work
  • Create tools for all stages of the simulation lifecycle including historical back-tests and production monitoring. Add new features to our simulators
  • Own visibility into GPU cluster utilization - track allocation, surface bottlenecks, and ensure our compute investment is being used effectively
  • Diagnose and resolve performance issues across training pipelines: data loading throughput, storage I/O, GPU utilization, and inter-node communication in distributed training runs
  • Build and maintain data pipelines that move financial data from storage into training workflows efficiently, with strong guarantees on correctness and versioning
  • Develop feature storage and retrieval patterns that support fast, reproducible access to training data at scale
  • Work directly with researchers to understand friction in their workflows, and build solutions that reduce it - from tooling improvements to infrastructure changes
  • Collaborate with existing infrastructure engineers on capacity planning, cloud/on-prem tradeoffs, and tooling decisions - this is a collaborative environment, not a siloed one
  • Stay current with developments in ML infrastructure tooling and bring relevant ideas and tools into our stack where they create genuine value

THE CANDIDATE

  • 5+ years of experience in ML engineering, research infrastructure, or HPC environments
  • Strong Python engineering skills - you write clean, maintainable, well-tested code that other engineers want to build on. Exposure to C++ in a performance-sensitive context is a plus
  • Experience building or operating distributed training infrastructure, with working knowledge of how collective communication libraries (NCCL, Horovod, or similar) behave at scale
  • Practical experience with experiment tracking systems and strong opinions about what good research infrastructure looks like
  • Comfort working across the Linux systems stack - storage, networking, job scheduling - enough to follow a problem wherever it leads
  • Excellent communication skills and the ability to work closely with researchers and engineers across disciplines
  • Intellectually curious and self-driven - you proactively identify problems worth solving, not just problems you've been asked to solve

DESIRED, BUT NOT REQUIRED

  • Experience with on-prem compute environments and job orchestration tools such as Slurm
  • Familiarity with GPU profiling tools (NSight Systems, PyTorch Profiler) and hands-on experience optimizing GPU memory or compute utilization
  • Experience with columnar data formats and high-performance data processing tools such as Parquet, Arrow, and Polars
  • Familiarity with workflow orchestration tools (Prefect, Dagster, or similar)
  • Prior experience in environments with high-stakes, time-series data at scale. Open to Quantitative Finance, Algorithmic Trading, and Other
  • Experience contributing to or extending open-source ML frameworks or infrastructure tooling

Salary Range: $200,000 - $300,000 (salary range is exclusive of bonuses, benefits or other categories of compensation)

Virtu Financial is an equal opportunity employer, committed to a diverse and inclusive workplace, welcoming you for who you are and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.