1

Ai Machine Learning Engineer Jobs in Stamford, CT

We are seeking a Machine Learning Engineer to join the High Frequency Trading Technology team ... This role will apply the latest AI technologies to solve various real-world problems and streamline ...

We are seeking a Machine Learning Engineer to join the High Frequency Trading Technology team ... This role will apply the latest AI technologies to solve various real-world problems and streamline ...

Stay up-to-date with the latest developments in machine learning and AI, and explore new techniques ... Strong programming skills in Python and familiarity with ML frameworks (like TensorFlow or PyTorch)

We are looking for a Machine Learning Engineer to help us create artificial intelligence products. Machine Learning Engineer responsibilities include creating machine learning models and retraining ...

We are building an AI-driven simulation software stack for engineering and manufacturing across ... Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who ...

About the Role We are looking for a Machine Learning Engineer, MLOps to help operationalize and ... Today, exacare ai powers more than 2,000 facilities, and is growing rapidly. We recently raised a ...

Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities ...

About the Position Our goals are to give you a real sense of what it's like to work at Jane Street as a Machine Learning Engineer while also providing a truly unparalleled educational experience. You ...

About the Position Our goals are to give you a real sense of what it's like to work at Jane Street as a Machine Learning Engineer while also providing a truly unparalleled educational experience. You ...

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

Machine Learning A leading provider of AI is looking for a Sr. ML Engineer. Our client is an industry leader in many different facets, such as: apps, games, devices, applications and digital ...

Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities ...

next page

Showing results 1-20

Ai Machine Learning Engineer information

See Stamford, CT salary details

$33.6K

$137.3K

$206.3K

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

As of Aug 24, 2026, the average yearly pay for ai 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.

What is an AI machine learning engineer?

An AI Machine Learning Engineer is a professional who designs, builds, and deploys artificial intelligence and machine learning models to solve real-world problems. They work with large datasets, select appropriate algorithms, and optimize models for accuracy and efficiency. Their role often involves both software engineering and data science skills, and they collaborate with other teams to integrate these models into products or services. AI Machine Learning Engineers are in high demand across industries such as technology, healthcare, finance, and more.

What are the key skills and qualifications needed to thrive as an AI machine learning engineer?

To thrive as an AI Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python or R), and a relevant degree such as computer science or engineering. Familiarity with frameworks like TensorFlow, PyTorch, and scikit-learn, as well as experience with cloud platforms and data processing tools, is highly valued, along with certifications in AI or machine learning. Critical thinking, problem-solving, and effective communication are essential soft skills for collaborating with teams and translating business needs into technical solutions. These competencies are crucial for developing accurate, scalable AI models that deliver real-world value and drive innovation.

What are some common challenges that AI machine learning engineers face when deploying models to production environments?

AI Machine Learning Engineers often encounter challenges such as ensuring model scalability, managing data pipeline reliability, and handling model drift once solutions are live. They also need to collaborate closely with DevOps and software engineering teams to integrate models seamlessly into existing systems, while maintaining performance and security. Addressing these challenges requires a strong understanding of both machine learning principles and software deployment best practices.

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

AspectAi Machine Learning EngineerData Scientist
CredentialsDegree in CS, AI, or related fields; certifications in ML frameworksDegree in CS, Statistics, or related fields; certifications in data analysis
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, where deploying ML models is keyResearch, business intelligence, analytics across industries

While both roles involve working with data and machine learning, Ai Machine Learning Engineers focus on building and deploying scalable ML models in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core focus and responsibilities.

Is AI Machine Learning Engineer in demand?

AI Machine Learning Engineers are in high demand due to the growing adoption of artificial intelligence across industries. They typically require skills in programming, data analysis, and familiarity with tools like TensorFlow or PyTorch, and job opportunities are expected to continue expanding as AI applications become more widespread.

What are popular job titles related to Ai Machine Learning Engineer jobs in Stamford, CT?

For Ai Machine Learning Engineer jobs in Stamford, CT, the most frequently searched job titles are:

Infographic showing various Ai Machine Learning Engineer job openings in Stamford, CT as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 2% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $137,303 per year, or $66 per hour.

Generative AI & Machine Learning Engineer

Morgan Stanley

New York, NY • On-site

$147K - $198K/yr

Full-time

Posted 18 days ago


Morgan Stanley rating

8.4

Company rating: 8.4 out of 10

Based on 155 frontline employees who took The Breakroom Quiz

33rd of 151 rated financial services


Job description

In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. This is a Generative AI & Machine Learning Engineering position at the Vice President level, which is part of the job family responsible for developing and maintaining software solutions that support business needs.


Morgan Stanley is an industry leader in financial services, known for mobilizing capital to help governments, corporations, institutions, and individuals around the world achieve their financial goals.


Interested in joining a team that's eager to create, innovate and make an impact on the world? Read on.

Technology works as a strategic partner with Morgan Stanley business units and the world's leading technology companies to redefine how we do business in ever more global, complex, and dynamic financial markets. Morgan Stanley's sizeable investment in technology results in quantitative trading systems, cutting-edge modeling and simulation software, comprehensive risk and security systems, and robust client-relationship capabilities, plus the worldwide infrastructure that forms the backbone of these systems and tools. Our insights, our applications and infrastructure give a competitive edge to clients' businesses-and to our own.


The Team:
The Investment Banking and Global Capital Markets Technology is a globally distributed but close-knit team based in NY, LN, Mumbai, Bengaluru and Pune. We are a highly innovative team that works in small groups that learn, grow, and succeed together. We follow Agile development practices to deliver high quality solutions that delight our customers. As a member of the team, you will interact with others who are genuine and want you to succeed. Your talent, experience, and voice are valued and will make a difference.


We are seeking an experienced and hands-on engineering leader specializing in Generative AI (GenAI), Large Language Models (LLMs), intelligent agents, and Machine Learning. This role is ideal for a technical leader who enjoys solving complex engineering problems, working closely with business and technology partners, and leading the end-to-end delivery of AI-powered products in a fast-paced investment banking environment.


What you'll do in the role:

  • Lead the end-to-end design, development, and delivery of enterprise AI and machine learning solutions from concept through production deployment.

  • Architect scalable, secure, and resilient AI platforms leveraging LLMs, Retrieval-Augmented Generation (RAG), intelligent agents, and modern machine learning techniques.

  • Provide hands-on technical leadership during solution design, implementation, code reviews, and production support.

  • Drive technical decision-making to ensure solutions are scalable, maintainable, and aligned with enterprise engineering standards.

  • Collaborate closely with product owners, business stakeholders, architects, and engineering teams to translate business requirements into high-quality technical solutions.

  • Lead technical planning, estimation, sprint execution, and delivery across multiple concurrent initiatives.

  • Ensure AI solutions are production-ready with appropriate monitoring, observability, testing, security, and operational support.

  • Drive engineering best practices including CI/CD, automated testing, code quality, infrastructure automation, and MLOps.

  • Evaluate emerging AI technologies and recommend practical adoption where they improve delivery or engineering productivity.

  • Mentor engineers and promote engineering excellence through technical guidance, design reviews, and knowledge sharing.

What you'll bring to the role:

  • 10+ years of AI/ML and software engineering experience, with a proven track record of designing, developing, and delivering production-grade AI solutions in enterprise environments.

  • Proven experience leading engineering teams and delivering complex technology initiatives in large enterprise environments.

  • Strong hands-on experience developing production-grade AI and machine learning applications.

  • Deep experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and agent-based architectures.

  • Strong programming skills in Python, with experience in Java or another enterprise programming language preferred.

  • Experience developing distributed systems using microservices, REST APIs, containerization, and cloud-native architectures.

  • Experience deploying AI applications using modern MLOps and DevOps practices.

  • Strong understanding of software engineering fundamentals including system design, scalability, resiliency, testing, and performance optimization.

  • Excellent communication skills with the ability to lead technical discussions across engineering and business teams.

  • Experience working in Agile software development environments.

  • Experience with OpenAI, Azure OpenAI, LangChain, LangGraph, or similar AI frameworks.

  • Experience with vector databases and Retrieval-Augmented Generation (RAG) architectures.

  • Experience building AI copilots, workflow automation, or agentic AI applications.

Preferred Qualifications

  • Experience within Investment Banking, Capital Markets, or Financial Services technology.

  • Experience with Kubernetes, Docker, GitHub Actions, Jenkins, MLflow, or similar DevOps and MLOps tooling.

  • Familiarity with cloud platforms such as Azure, AWS, or Google Cloud


WHAT YOU CAN EXPECT FROM MORGAN STANLEY:

At Morgan Stanley, we raise, manage and allocate capital for our clients - helping them reach their goals. We do it in a way that's differentiated - and we've done that for 90 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren't just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you'll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There's also ample opportunity to move about the business for those who show passion and grit in their work.

To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser.

Expected base pay rates for the role will be between $155,000 and $215,000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.

Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.

Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.

For more information, please visit: https://www.morganstanley.com/people-opportunities/eeo.


What Morgan Stanley employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Morgan Stanley logo

About Morgan Stanley

Sourced by ZipRecruiter

Since our founding in 1935, Morgan Stanley has been committed to serving local and global communities by being a market leader in Investment Banking, Securities, Investment Management and Wealth Management services. Our belief that capital can work to benefit all of society inspires us to put our clients first, lead with exceptional ideas, hold our business to high ethical standards, and give back to communities around the world through philanthropy and public works. We have a smart casual dress code and operate under a philosophy that balances work with your personal life. Our people's talent, passion, and expertise is the fuel on which our organization runs, therefore, our people are our greatest asset. Diversity and inclusiveness is a critical component for our success and it is our priority to continue building a firm that values the unique background and identity of every one of our employees, thus enabling our people to bring their full, and best selves to work each day. Teamwork is the essence of our approach, and so are the values of integrity, excellence, and enabling our people to achieve at the highest levels. We invite you to learn more about our commitment to diversity and serving our community.

Industry

Finance and insurance and software development

Company size

10,000+ Employees

Headquarters location

New York, NY, US