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Internship Machine Learning Startup Jobs (NOW HIRING)

Machine Learning Engineer

Somerville, MA · On-site +1

$170K - $200K/yr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice ... Experience in fast-paced startup environments Benefits * Competitive salary + equity * Full health ...

New

... Startup. Our Culture Shipwell is a fast-paced, high-energy start-up that strives to build the ... About the Role As a Machine Learning Engineer at Shipwell, you'll play a pivotal role in building ...

To be successful you should have 0-3 years of of professional or internship experience in machine learning, data science, or software engineering. Also proficiency in Python and familiarity with ML ...

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Internship Machine Learning Startup information

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$25.5K

$42.6K

$88K

How much do internship machine learning startup jobs pay per year?

As of Jun 26, 2026, the average yearly pay for internship machine learning startup in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is the difference between Internship Machine Learning Startup vs Data Science Intern?

AspectInternship Machine Learning StartupData Science Intern
Required CredentialsBasic programming, statistics, coursework in MLSimilar; often includes coursework in data analysis and statistics
Work EnvironmentFast-paced startup, collaborative teamsVaries; startups or corporate settings, collaborative
Industry UsageCommon in tech startups focusing on AI/ML productsWidespread across tech, finance, healthcare
Search & Comparison IntentInterested in ML-specific roles in startupsLooking for data analysis or data science internships

Internship Machine Learning Startup roles focus on applying ML techniques in startup environments, often requiring programming and statistical skills. Data Science Internships may encompass broader data analysis tasks across various industries. Both roles share similar credentials and work environments, but ML internships are more specialized in machine learning applications within startups.

More about Internship Machine Learning Startup jobs
What cities are hiring for Internship Machine Learning Startup jobs? Cities with the most Internship Machine Learning Startup job openings:
What are the most commonly searched types of Machine Learning Startup jobs? The most popular types of Machine Learning Startup jobs are:
What states have the most Internship Machine Learning Startup jobs? States with the most job openings for Internship Machine Learning Startup jobs include:
Infographic showing various Internship Machine Learning Startup job openings in the United States as of June 2026, with employment types broken down into 2% Internship, 87% Full Time, 8% Part Time, and 3% Nights. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Machine Learning Engineer

Machine Learning Engineer

Modulate

Somerville, MA • On-site, Remote

$170K - $200K/yr

Full-time

Medical, Dental, Vision, PTO

Posted yesterday


Job description

Modulate is the leader in conversational voice intelligence. We enable enterprises to deeply understand how people communicate and take timely action based on those insights. Our products help detect harm, prevent fraud, and build safer, more trusted online and real-world voice environments. We are building a Conversation Intelligence Platform - APIs, workflows, and applications that bring voice understanding to customers at enterprise scale.

We're looking for a Senior Machine Learning Engineer to help advance the state of voice understanding at Modulate. In this role, you'll design, train, evaluate, and deploy cutting-edge machine learning models that power our products. You'll work closely with researchers, engineers, product leaders, and executives to bring innovative ML solutions from concept to production.

Your Impact
  • Develop and deploy high-quality machine learning models that power Modulate's products
  • Advance our capabilities in conversational voice intelligence through applied research and engineering
  • Help translate business needs into scalable ML solutions
  • Improve model performance, reliability, and efficiency across our platform
  • Contribute to a collaborative, high-performing engineering culture
What You Will Do
  • Design, train, evaluate, and deploy machine learning models for production applications
  • Collaborate with engineers, researchers, product managers, and company leadership to define and execute on ML initiatives
  • Conduct experiments to improve model quality, accuracy, robustness, and scalability
  • Partner with platform and infrastructure teams to operationalize and monitor ML systems in production
  • Analyze model performance and identify opportunities for improvement
  • Communicate technical findings, tradeoffs, and recommendations to both technical and non-technical stakeholders
  • Contribute to technical strategy and help shape the future direction of Modulate's ML systems
  • Review code, share knowledge, and mentor teammates as needed
  • Stay current on advances in machine learning and identify opportunities to apply new techniques to our products
What We Are Looking For
  • Experience conducting machine learning research and shipping models to production
  • Strong experience building and deploying production-grade machine learning systems
  • Strong experience with Python and PyTorch
  • Experience designing experiments and evaluating model performance
  • Ability to work across research and engineering disciplines to deliver business impact
  • Strong communication skills and the ability to explain complex technical concepts clearly
  • Experience working collaboratively in cross-functional environments
Nice to Have
  • Experience communicating research externally through papers, conferences, or open-source contributions
  • Experience with audio models or speech systems (ASR, TTS, speaker modeling, etc.)
  • Experience with cloud infrastructure, especially AWS
  • Experience building and maintaining large-scale ML infrastructure or MLOps systems
  • Experience in fast-paced startup environments
Benefits
  • Competitive salary + equity
  • Full health, dental, and vision coverage
  • Flexible PTO with a strong culture of taking it
  • Weekly team lunches with dietary accommodations
  • Hybrid work with core in-office days and flexible remote options
  • Leadership and technical learning sessions
  • Career development and continued growth support
  • Up to 8 weeks work-from-anywhere policy
  • A deeply inclusive, human-centered culture
Pay Transparency

Modulate believes in transparency as a cornerstone of equity and trust. Compensation for this role is based on seniority, skills, and experience.

Salary: $170,000-$200,000
Equity: Offered

Additional benefits include HSA, FSA, 15 company holidays, and professional development resources.

Candidates may be located anywhere in the U.S., with preference for proximity to major tech hubs such as Boston, San Francisco, Seattle, New York, or Austin.

About Modulate

Modulate is on a mission to make voice a force for good online. Our tools help communities thrive by proactively detecting toxic behavior, protecting user identity, and empowering safety teams. We're trusted by leaders in gaming and beyond-and we're growing fast.

We believe that great cultures don't just happen. That's why we've built a foundation of intentional systems: from bias-reducing hiring practices to transparent pay to tools that help teams collaborate across communication styles. At Modulate, we treat people like people-and we're building technology that does the same.

Ready to join us? Apply here or reach out directly-we're excited to meet you.

A Quick Note as You Apply
  • Please apply through the website rather than emailing [email protected].
  • For application questions ("Your fit for the role," "Your values/goals," and "Why Modulate?"), focus on relevant experience and motivations.
  • Avoid including protected demographic information.
  • Keep responses authentic and in your own voice.
$170,000 - $200,000 a year
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. 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.
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