2

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

Senior Machine Learning Engineer

New York, NY ยท On-site +1

$134K - $176K/yr

We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth. If working in an environment that encourages you to innovate and ...

Senior Machine Learning Engineer

New York, NY ยท On-site +1

$145K - $209K/yr

You enjoy working with a diverse group of people with different experiences and take pride in mentoring and learning from others Our stack You do not need experience with all of these, but we thought ...

MLOps Engineer

New York, NY ยท On-site +1

We have a flexible work environment and allow remote work depending on one's personal choice. Responsibilities: As the Machine Learning Ops Engineer for the AI Team you will: * Work closely with the ...

Senior Software Engineer - Remote

New York, NY ยท Remote

$134K - $176K/yr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Familiarity with modern AI or machine learning systems is a plus, though not required. * Background ...

Showing results 21-40

Remote Machine Learning information

See Stamford, CT salary details

$27.2K

$45.4K

$93.8K

How much do remote machine learning jobs pay per year?

As of Aug 10, 2026, the average yearly pay for remote machine learning in Stamford, CT is $45,406.00, according to ZipRecruiter salary data. Most workers in this role earn between $34,700.00 and $49,000.00 per year, depending on experience, location, and employer.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a machine learning engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

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

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Can remote machine learning engineers work remotely?

Yes, remote machine learning engineers can work remotely, as many companies offer flexible work arrangements for data science and AI roles. These positions typically require strong programming skills, experience with tools like Python and TensorFlow, and the ability to collaborate virtually using communication platforms. Remote work in this field is common, especially for roles focused on model development, data analysis, and deployment.
What are popular job titles related to Remote Machine Learning jobs in Stamford, CT? For Remote Machine Learning jobs in Stamford, CT, the most frequently searched job titles are:
What cities near Stamford, CT are hiring for Remote Machine Learning jobs? Cities near Stamford, CT with the most Remote Machine Learning job openings:
Infographic showing various Remote Machine Learning job openings in Stamford, CT as of August 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% Remote job distribution, with an average salary of $45,406 per year, or $21.8 per hour.

Senior Machine Learning Engineer, Surfaces Moments

Spotify

New York, NY โ€ข Remote

$184K - $262K/yr

Full-time

Posted 18 days ago


Job description

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.

Surfaces Moments is a ML team within the Personalization Mission focused on creating moment-based experiences across Spotify surfaces. The team owns and evolves the experiences that help listeners quickly connect with the content that matters most to them, including the Home Shortcuts experience and the underlying intelligence that powers it. By combining cutting-edge machine learning, recommendation systems, and product thinking, the team delivers highly relevant, personalized experiences to millions of listeners around the world.

As a Senior Machine Learning Engineer, you will help shape the future of personalized discovery and engagement at Spotify. You’ll work at the intersection of recommendation systems, large language models, and production-scale machine learning infrastructure to build experiences that delight users and drive meaningful impact. This role is ideal for someone who enjoys taking models from research to production, collaborating across disciplines, and solving complex personalization challenges at global scale.

What You'll Do
  • Own and improve the machine learning models and systems that power the Home feed, including the Shortcuts experience.
  • Design, build, and ship personalized recommendations that serve millions of Spotify listeners globally.
  • Build content recommendation systems for emerging agentic and AI-powered user experiences.
  • Train, fine-tune, evaluate, and optimize large language models using techniques such as supervised fine-tuning (SFT), distillation, and parameter-efficient training approaches.
  • Partner closely with product managers, engineers, data scientists, and designers to define and execute experimentation strategies.
  • Drive A/B testing, monitoring, model evaluation, and continuous optimization of recommendation quality, reliability, and cost efficiency.
  • Improve ML platform capabilities, data pipelines, and production systems that support personalization at Spotify scale.
Who You Are
  • You have 5+ years of experience building and deploying machine learning systems in production environments.
  • You have deep expertise in recommendation systems, ranking models, personalization, or large-scale content discovery platforms.
  • You have strong proficiency in Python and hands-on experience building machine learning systems with PyTorch.
  • You are experienced with large language model training, fine-tuning, evaluation, and optimization techniques including SFT, distillation, and LoRA.
  • You have worked with large-scale inference systems and understand the challenges of latency, reliability, and cost optimization.
  • You care deeply about creating high-quality user experiences through thoughtful application of machine learning.
  • You communicate effectively across technical and non-technical audiences and enjoy working in highly collaborative environments.
  • You know how to design, execute, and interpret online experiments and A/B tests to improve user outcomes.
  • You have experience operating distributed machine learning workloads using technologies such as Ray, FSDP, HSDP, or similar frameworks.
  • You are experienced building and maintaining data pipelines and orchestration workflows using technologies such as Flyte, Airflow, BigQuery, and cloud-based storage platforms.
Where You'll Be
  • We offer you the flexibility to work where you work best! For this role, you can be within the North Americas region as long as we have a work location.
  • This team operates within the Eastern Standard time zone for collaboration.

The United States base range for this position is $184,050 $262,928 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future.


Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
 
At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.
 

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice