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Federated Learning Phd Jobs (NOW HIRING)

Jobs for Humanity

Machine Learning Engineers

San Jose, CA · On-site

$194K - $355K/yr

... PhD or Master's degree in Computer Science or a related field, or 3+ years of experience working in related fields - Familiar with federated learning / distributed machine learning algorithms and ...

Pluralis

Academic Collaboration

Sydney, FL · On-site

$88K - $112K/yr

Current faculty, postdocs, or PhD candidates actively publishing in relevant fields. * Relevant Expertise: Background in distributed ML, model parallelism, federated learning, or related areas.

Centific

Technical Intern

$40/hr

Federated Learning / Differential Privacy * Red Teaming * ML Ops * LLM Ops / Observability 💡 ... PhD / MS / M Tech candidates with a zeal for research and innovation * Individuals eager to work on ...

webAI

AI Research Scientist

Austin, TX · On-site

... or PhD in Machine Learning, Computer Science, AI, or a related field • Experience with ... federated learning • Experience contributing to academic publications, patents, or open-source ML ...

webAI

AI Research Scientist

Austin, TX · On-site

... or PhD in Machine Learning, Computer Science, AI, or a related field • Experience with ... federated learning • Experience contributing to academic publications, patents, or open-source ML ...

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How much do federated learning phd jobs pay per hour?

As of Jun 8, 2026, the average hourly pay for federated learning phd in the United States is $32.69, according to ZipRecruiter salary data. Most workers in this role earn between $21.63 and $43.27 per hour, depending on experience, location, and employer.

What are some common challenges faced by a Federated Learning PhD in collaborative research environments?

As a Federated Learning PhD, you'll often work at the intersection of machine learning, privacy, and distributed systems, collaborating with interdisciplinary teams. A key challenge is addressing data heterogeneity and ensuring model robustness across diverse, decentralized datasets. Coordinating experiments across multiple organizations or devices while maintaining privacy and security can be complex. Effective communication and project management skills are essential to align research goals and integrate feedback from collaborators in academia or industry.

What is the difference between Federated Learning Phd vs Data Scientist?

AspectFederated Learning PhdData Scientist
Required CredentialsPhD in Computer Science, Machine Learning, or related fieldBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentResearch-focused, often in academia or R&D departmentsIndustry settings, analytics teams, product development
Industry UsageSpecialized research projects, AI development, privacy-preserving MLData analysis, modeling, business insights, product optimization

Federated Learning Phds typically focus on advanced research in privacy-preserving machine learning, requiring a PhD and a strong background in AI. Data Scientists work across industries analyzing data to inform business decisions, often with a Bachelor's or Master's degree. While both roles involve machine learning, Federated Learning Phds are more research-oriented, whereas Data Scientists focus on applied data analysis.

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

To thrive as a Federated Learning PhD, you need deep expertise in machine learning, distributed systems, and data privacy, typically supported by a PhD in computer science or related fields. Proficiency with Python, TensorFlow, PyTorch, and specialized federated learning frameworks, as well as knowledge of secure aggregation and privacy-enhancing technologies, is essential. Strong research, problem-solving, and communication skills help you navigate complex challenges and collaborate effectively in academia or industry. These skills ensure the ability to advance federated learning techniques and deliver scalable, privacy-preserving AI solutions.

What is a Federated Learning PhD?

A Federated Learning PhD refers to a doctoral research position or program focused on federated learning, a machine learning approach where models are trained collaboratively across multiple devices or servers while keeping the underlying data decentralized and private. This research typically explores new algorithms, privacy-preserving techniques, system architectures, and applications of federated learning in fields like healthcare, finance, and edge computing. A PhD in this area involves both theoretical study and practical experiments, preparing graduates for advanced roles in academia or industry related to privacy-aware artificial intelligence.

Machine Learning Engineers

Jobs for Humanity

San Jose, CA • On-site

$194K - $355K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 21 days ago

Job description

Company Description
Jobs for Humanity is collaborating with Upwardly Global and with Tiktok to build an inclusive and just employment ecosystem. We support individuals coming from all walks of life.
Company Name: Tiktok
Job Description

Senior Research Engineer, Machine Learning
Privacy
San Jose
Regular
R D
Machine learning
Job ID: M1758
Responsibilities
TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and its offices include New York, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.
Why Join Us
Creation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible. Together, we inspire creativity and bring joya mission we all believe in and aim towards achieving every day. To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always.
At TikTok, we create together and grow together. That's how we drive impactfor ourselves, our company, and the communities we serve. Join us.
At TikTok, we treat privacy as our first priority in our product design and implementation. Privacy is not just about regulation compliance, but also about a more trusted way to enable technology innovation by respecting users' privacy choices! Privacy Innovation (PI) Lab is established to explore the next frontier of privacy technology and theory in the digitalized world. We provide key insights and technical solutions on privacy-related innovation for all TikTok's products. Furthermore, we also collaborate with worldwide technical and academic communities to build an open ecosystem to promote privacy friendly digital experience. PI Lab is growing fast and seeking highly experienced, bright, and capable researchers and professionals to join our team. As a member of PI Lab, you will have the opportunities to research advanced privacy technology and theory together with worldwide influential researchers, and to tackle the critical industrial challenges on privacy innovation serving billions of TikTok users by applying cutting-edge technology.
Responsibilities
- Participate in the construction of a multi-party joint modeling and data analysis platform
- Work with product teams to understand key privacy requirements from TikTok product family and convert research outcomes into technical solutions and product prototypes
- Work with research teams for complex experiments requiring optimized algorithms running on large datasets or sophisticated data processing
- Build open-source tools and infrastructure for privacy related research and engage with community contributors in external events including meetups, hackathons, summits
Qualifications
Minimum Requirements:
- PhD or Master's degree in Computer Science or a related field, or 3+ years of experience working in related fields
- Familiar with federated learning / distributed machine learning algorithms and experienced in federated learning frameworks and applications development
- Familiar with machine learning and deep learning frameworks, like TensorFlow, Pytorch, JAX
- Interest in privacy-enhanced techniques (PET) and related technical domains, including data and identity anonymization, differential privacy, secure multi-party computation, federated machine learning, on-device machine learning, interpretable AI, privacy-preserving technology for large language models (LLM) or foundation models, privacy-preserving regulation technology, etc.
- Proficiency in at least one of the following programming languages, Go, C++, Python, Rust, Java
- Ability to work globally and collaboratively within a team
TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too. TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at https://shorturl.at/cdpT2
Job Information
For Pay Transparency
Compensation Description (annually) The base salary range for this position in the selected city is $194,000 - $355,000 annually. Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units. Our company benefits are designed to convey company culture and values, to create an efficient and inspiring work environment, and to support our employees to give their best in both work and life. We offer the following benefits to eligible employees:
- We cover 100% premium coverage for employee medical insurance, approximately 75% premium coverage for dependents and offer a Health Savings Account(HSA) with a company match
- Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life and AD&D insurance plans
- Flexible Spending Account(FSA) Options like Health Care, Limited Purpose and Dependent Care
- 10 paid holidays per year plus 17 days of Paid Personal Time Off (PPTO) (prorated upon hire and increased by tenure) and 10 paid sick days per year as well as 12 weeks of paid Parental leave and 8 weeks of paid Supplemental Disability
- Mental and emotional health benefits through our EAP and Lyra
- 401K company match, gym and cellphone service reimbursements
The Company reserves the right to modify or change these benefits programs at any time, with or without notice. For Los Angeles County (unincorporated) Candidates:
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:
1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues
2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems
3. Exercising sound judgment

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