Entry Level Lead Machine Learning Engineer Jobs
New grad lead machine learning engineer jobs are open to recent graduates and entry level candidates with zero to two years of experience, where a strong portfolio or internship work can matter more than a long resume. Most openings are Technology & Software, Social Media, and Science & Research roles with a mix of on-site, remote, and hybrid settings, and employers like TikTok, Pinterest, and TikTok USDS Joint Venture are hiring at this level now.
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Showing 5 of 104+ Entry Level Lead Machine Learning Engineer jobs
Responsibilities
About the Team
We are a group of applied machine learning engineers that focus on TikTok recommendations and search engineers powering multiple product areas such as For-You-Page (FYP), Live Streaming, Global E-commerce, Local Services and more. We are developing innovative algorithms and techniques to improve user engagement and satisfaction, converting creative ideas into business-impacting solutions. We are interested in and excited about pushing the envelope of State-of-the-Art (SOTA) large scale machine learning to solve various real-world problems.
What You'll Do
- Technical Execution & System Ownership: Contribute to the technical roadmap and hands-on implementation of our large-scale (in billions parameters) distributed real-time ML training and inferencing platforms that power the TikTok recommendation and search engines, Short Form Video (SFV) ecosystem. Have a direct business impact on Live, Global E-Commerce, Local Services and many business domains.
- Large-Scale Parallelism Architecture: Help design and scale multi-node distributed training systems, implementing advanced 3D parallelism strategies (Data, Tensor, Pipeline) to maximize compute efficiency and model scalability. Participate in the architecture, scale-testing, and maintenance of massive distributed computing foundations, GPU cluster configurations, and orchestration pipelines to achieve high hardware utilization and cluster efficiency under established SLI/SLO frameworks.
- Production Inference & Serving: Build and scale low-latency, high-throughput model serving infrastructure, optimizing inference pipelines and leveraging low-level execution paths to handle massive live traffic under strict boundary isolation.
- Algorithm-Infrastructure Co-Design: Partner closely with Applied ML Research teams to co-design and pioneer next-generation Generative Recommendation systems, abstracting general-purpose components to support advanced generative paradigms in production.
- Resiliency & Fault Tolerance: Build robust, automated fault-detection systems and asynchronous checkpointing mechanisms to gracefully handle hardware drops, silent data corruption (SDC), or network-switch failures in multi-thousand GPU clusters.
- Cross-Functional Collaboration: Partner with Applied ML researchers and data platform teams to engineer high-throughput, secure multi-modal data processing and storage engines that prevent compliance friction.
- Security & Compliance Hardening: Implement and enforce strict encryption-at-rest/in-transit controls, access control lists (ACLs), and secure tenant isolation protocols across the entire compute stack to meet compliance objectives.
Qualifications
Minimum Qualifications
- Bachelor’s or Master's degree in Computer Science, Computer Engineering, or a related technical discipline.
- 2+ years of professional software engineering experience with deep expertise in Python, C++/Java
- 1+ years of direct experience building and maintaining machine learning infrastructure at enterprise scale
- Deep technical familiarity with the internals of core ML frameworks (PyTorch / TensorFlow) and a strong understanding of low-level GPU memory management, CUDA interactions, and networking topologies (InfiniBand/RoCE).
- Solid understanding of production-grade LLM training and inference tools, with hands-on profiling skills to eliminate I/O, compute, or network bottlenecks.
- Strong system-level troubleshooting and debugging skills, with experience profiling and eliminating I/O, compute, or network bottlenecks.
Preferred Qualifications
- Experience optimizing high-performance training loops to maximize Model Flops Utilization (MFU) through advanced communication-computation overlap and zero-bubble pipeline scheduling across large-scale distributed clusters using industry-standard frameworks (e.g., Megatron, DeepSpeed).
- Proven track record of scaling LLM training or inference workloads across hundreds of GPUs, with deep familiarity in advanced serving techniques such as KV Cache management, Prefill-Decoding (PD) separation, and model quantization.
- Experience working in highly regulated industries, sovereign cloud environments, or dealing with federal data security compliance frameworks.
- Strong flavor in low-level kernel development and graph compilation, with experience in CUDA, Triton, Cutlass, TensorRT, or Triton Inference Server being a huge plus.
- Active background or interest in keeping up with the latest industry breakthroughs in MLOps, MoE (Mixture of Experts) routing infrastructure, and specialized hardware optimization.
- Strong communication skills, with the ability to collaborate effectively across team boundaries, draft clear technical design docs, and mentor team members.
About USDS
TikTok USDS Joint Venture LLC is dedicated to the safety and security of millions of Americans who create, discover, and connect with what they love on the apps we operate. The Joint Venture has been established in compliance with the Executive Order signed by President Trump on September 25, 2025. Our foundation is a comprehensive data privacy and cybersecurity program we operate under defined safeguards to protect national security and secure U.S. user data, apps and the algorithm. We safeguard the U.S. content ecosystem, holding decision-making authority for trust and safety policies and moderation. USDS Joint Venture helps ensure Americans can continue to express their creativity, discover new hobbies and interests, and build thriving communities and businesses on a global scale.
On-site presence across teams allows the company to operate with greater speed, alignment, and agility — especially in areas like real-time decision-making, team development, and integrated execution. As such, the company is shifting from a hybrid work model to a fully in-person schedule up to 5 days a week.
Why Join Us
Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy – a mission we work towards every day. We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.
Diversity & Inclusion
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.
USDS Reasonable Accommodation
USDS 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://tinyurl.com/USDS-RA
Job Information
【For Pay Transparency】Compensation Description (Annually) The base salary range for this position in the selected city is $129960 - $246240 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.
Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).
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; and
3. Exercising sound judgment.
Responsibilities
About the Team
We are a group of applied machine learning engineers that focus on TikTok recommendations and search engineers powering multiple product areas such as For-You-Page (FYP), Live Streaming, Global E-commerce, Local Services and more. We are developing innovative algorithms and techniques to improve user engagement and satisfaction, converting creative ideas into business-impacting solutions. We are interested in and excited about pushing the envelope of State-of-the-Art (SOTA) large scale machine learning to solve various real-world problems.
What You'll Do
- Technical Execution & System Ownership: Contribute to the technical roadmap and hands-on implementation of our large-scale (in billions parameters) distributed real-time ML training and inferencing platforms that power the TikTok recommendation and search engines, Short Form Video (SFV) ecosystem. Have a direct business impact on Live, Global E-Commerce, Local Services and many business domains.
- Large-Scale Parallelism Architecture: Help design and scale multi-node distributed training systems, implementing advanced 3D parallelism strategies (Data, Tensor, Pipeline) to maximize compute efficiency and model scalability. Participate in the architecture, scale-testing, and maintenance of massive distributed computing foundations, GPU cluster configurations, and orchestration pipelines to achieve high hardware utilization and cluster efficiency under established SLI/SLO frameworks.
- Production Inference & Serving: Build and scale low-latency, high-throughput model serving infrastructure, optimizing inference pipelines and leveraging low-level execution paths to handle massive live traffic under strict boundary isolation.
- Algorithm-Infrastructure Co-Design: Partner closely with Applied ML Research teams to co-design and pioneer next-generation Generative Recommendation systems, abstracting general-purpose components to support advanced generative paradigms in production.
- Resiliency & Fault Tolerance: Build robust, automated fault-detection systems and asynchronous checkpointing mechanisms to gracefully handle hardware drops, silent data corruption (SDC), or network-switch failures in multi-thousand GPU clusters.
- Cross-Functional Collaboration: Partner with Applied ML researchers and data platform teams to engineer high-throughput, secure multi-modal data processing and storage engines that prevent compliance friction.
- Security & Compliance Hardening: Implement and enforce strict encryption-at-rest/in-transit controls, access control lists (ACLs), and secure tenant isolation protocols across the entire compute stack to meet compliance objectives.
Qualifications
Minimum Qualifications
- Bachelor’s or Master's degree in Computer Science, Computer Engineering, or a related technical discipline.
- 2+ years of professional software engineering experience with deep expertise in Python, C++/Java
- 1+ years of direct experience building and maintaining machine learning infrastructure at enterprise scale
- Deep technical familiarity with the internals of core ML frameworks (PyTorch / TensorFlow) and a strong understanding of low-level GPU memory management, CUDA interactions, and networking topologies (InfiniBand/RoCE).
- Solid understanding of production-grade LLM training and inference tools, with hands-on profiling skills to eliminate I/O, compute, or network bottlenecks.
- Strong system-level troubleshooting and debugging skills, with experience profiling and eliminating I/O, compute, or network bottlenecks.
Preferred Qualifications
- Experience optimizing high-performance training loops to maximize Model Flops Utilization (MFU) through advanced communication-computation overlap and zero-bubble pipeline scheduling across large-scale distributed clusters using industry-standard frameworks (e.g., Megatron, DeepSpeed).
- Proven track record of scaling LLM training or inference workloads across hundreds of GPUs, with deep familiarity in advanced serving techniques such as KV Cache management, Prefill-Decoding (PD) separation, and model quantization.
- Experience working in highly regulated industries, sovereign cloud environments, or dealing with federal data security compliance frameworks.
- Strong flavor in low-level kernel development and graph compilation, with experience in CUDA, Triton, Cutlass, TensorRT, or Triton Inference Server being a huge plus.
- Active background or interest in keeping up with the latest industry breakthroughs in MLOps, MoE (Mixture of Experts) routing infrastructure, and specialized hardware optimization.
- Strong communication skills, with the ability to collaborate effectively across team boundaries, draft clear technical design docs, and mentor team members.
About USDS
TikTok USDS Joint Venture LLC is dedicated to the safety and security of millions of Americans who create, discover, and connect with what they love on the apps we operate. The Joint Venture has been established in compliance with the Executive Order signed by President Trump on September 25, 2025. Our foundation is a comprehensive data privacy and cybersecurity program we operate under defined safeguards to protect national security and secure U.S. user data, apps and the algorithm. We safeguard the U.S. content ecosystem, holding decision-making authority for trust and safety policies and moderation. USDS Joint Venture helps ensure Americans can continue to express their creativity, discover new hobbies and interests, and build thriving communities and businesses on a global scale.
On-site presence across teams allows the company to operate with greater speed, alignment, and agility — especially in areas like real-time decision-making, team development, and integrated execution. As such, the company is shifting from a hybrid work model to a fully in-person schedule up to 5 days a week.
Why Join Us
Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy – a mission we work towards every day. We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.
Diversity & Inclusion
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.
USDS Reasonable Accommodation
USDS 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://tinyurl.com/USDS-RA
Job Information
【For Pay Transparency】Compensation Description (Annually) The base salary range for this position in the selected city is $129960 - $246240 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.
Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).
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; and
3. Exercising sound judgment.
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Find JobsEntry Level Lead Machine Learning Engineer Job Market
Who's Hiring
- TikTok15
- Pinterest8
- TikTok USDS Joint Venture6
- Uber3
- Abridge3
Top Industries Hiring
- Technology & Software61
- Social Media6
- Science & Research6
- Electronics & Hardware6
- Artificial Intelligence6
Entry Level Lead Machine Learning Engineer Jobs: Frequently Asked Questions
How do I get an entry level lead machine learning engineer job?
Build a portfolio that shows applied machine learning work, such as end-to-end projects on GitHub covering data preprocessing, model training, and evaluation. Employers hiring at the entry level look for hands-on evidence of Python fluency, experience with frameworks like TensorFlow or PyTorch, and familiarity with MLOps basics. Internship experience or bootcamp projects that demonstrate real problem-solving give candidates a clear edge over a plain resume.
Which companies hire entry level lead machine learning engineers?
Companies hiring entry level lead machine learning engineers right now include TikTok, Pinterest, and TikTok USDS Joint Venture, based on current listings on Migrate Mate as of November 2026. At this level, hiring comes from a mix of tech-forward enterprises, AI-focused startups, and large organizations building out their first dedicated machine learning functions.
Are there remote entry level lead machine learning engineer jobs?
Yes, though availability varies by employer and role. About 23% of entry level lead machine learning engineer openings are remote or hybrid as of November 2026, with fully remote roles more common at startups and hybrid arrangements typical at larger organizations that want new engineers on-site for onboarding and team collaboration.
Are these new grad lead machine learning engineer jobs?
Yes, these listings include new grad, recent graduate, and junior roles alongside other entry level postings. A new grad-friendly posting typically welcomes zero to two years of experience, accepts internships or academic projects as qualifying experience, and does not require prior professional machine learning deployments. Look for language like 'new grads welcome' or 'portfolio in lieu of experience' as strong signals.
Which industries hire the most entry level lead machine learning engineers?
Entry Level lead machine learning engineer roles concentrate in Technology & Software, Social Media, and Science & Research, based on current listings on Migrate Mate as of November 2026. Those sectors drive hiring at this level because they are actively building out machine learning pipelines and need junior engineers who can contribute to model development and data infrastructure from day one.