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Research Machine Learning Federated Learning Jobs in Massachusetts

Machine Learning Engineer

Somerville, MA · On-site

$170K - $200K/yr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice ... You'll work closely with researchers, engineers, product leaders, and executives to bring ...

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 ... You'll work closely with researchers, engineers, product leaders, and executives to bring ...

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 ... You'll work closely with researchers, engineers, product leaders, and executives to bring ...

The work is highly collaborative and spans quantitative research, software engineering, and machine learning. Analysts work with other members of the machine learning team and portfolio managers to ...

Machine Learning Analyst

Boston, MA · On-site

$110K - $145K/yr

The work is highly collaborative and spans quantitative research, software engineering, and machine learning. Analysts work with other members of the machine learning team and portfolio managers to ...

We are currently looking for a Machine Learning Scientist/Researcher to join our team. We would like to advance our current methods of identifying brain activity, using novel machine learning ...

We are currently looking for a Machine Learning Scientist/Researcher to join our team. We would like to advance our current methods of identifying brain activity, using novel machine learning ...

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Showing results 1-20

Research Machine Learning Federated Learning information

What are the key skills and qualifications needed to thrive as a Researcher in Machine Learning Federated Learning, and why are they important?

To thrive as a Researcher in Machine Learning Federated Learning, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant advanced degree (e.g., PhD or MSc). Familiarity with Python, TensorFlow, PyTorch, and distributed computing frameworks, as well as knowledge of privacy-preserving techniques and relevant research publications, is essential. Excellent analytical thinking, problem-solving abilities, and clear scientific communication are key soft skills for success in collaborative research environments. These competencies are vital to drive innovation, rigorously evaluate federated learning approaches, and advance privacy-preserving AI technologies.

What are some common challenges faced when implementing federated learning in a research environment?

One of the primary challenges in research-focused federated learning roles is ensuring data privacy and security while maintaining model performance across distributed devices. Researchers must also address issues such as handling heterogeneous data sources, communication bottlenecks between nodes, and the complexity of debugging decentralized systems. Collaborating with cross-functional teams—such as data engineers, privacy experts, and domain specialists—is vital to overcome these hurdles and drive successful outcomes. Staying updated with the latest advancements and actively contributing to open-source initiatives can also help researchers address these evolving challenges.

What is a Researcher in Machine Learning Federated Learning?

A Researcher in Machine Learning Federated Learning is a professional who investigates and develops methods to train machine learning models across multiple decentralized devices or servers, while keeping data localized and private. Their work focuses on improving algorithms, ensuring data privacy, and addressing challenges related to distributed learning, communication efficiency, and model accuracy. They often collaborate with other researchers, publish findings, and contribute to advancing technologies that make it possible to use sensitive data for AI without compromising privacy.

What is the difference between Research Machine Learning Federated Learning vs Data Scientist?

AspectResearch Machine Learning Federated LearningData Scientist
CredentialsAdvanced degrees in CS, ML, or related fields; research experienceBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, academic institutions, tech companies focusing on privacy-preserving MLBusiness environments, analytics teams, data-driven departments
Industry UsageDeveloping federated algorithms, privacy-preserving ML modelsData analysis, modeling, reporting, and insights generation

Research Machine Learning Federated Learning specialists focus on developing privacy-preserving algorithms across distributed data sources, often in research or R&D settings. Data Scientists analyze and interpret data to inform business decisions. While both roles require strong ML knowledge, federated learning roles emphasize distributed systems and privacy, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Research Machine Learning Federated Learning jobs in Massachusetts? For Research Machine Learning Federated Learning jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Research Machine Learning Federated Learning jobs in Massachusetts look for? The top searched job categories for Research Machine Learning Federated Learning jobs in Massachusetts are:
What cities in Massachusetts are hiring for Research Machine Learning Federated Learning jobs? Cities in Massachusetts with the most Research Machine Learning Federated Learning job openings:
Machine Learning Engineer

Machine Learning Engineer

Modulate

Somerville, MA • On-site

$170K - $200K/yr

Full-time

Medical, Dental, Vision, PTO

Posted 2 days ago


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.