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Internship Full Stack Machine Learning Engineer Jobs

Avride

Machine Learning Engineer Internship

Austin, TX · On-site

... stack. What You'll Do We are currently offering four different internships within our Perception ... Machine Learning / Math Foundation: Strong understanding of deep learning, reinforcement learning ...

Strava

Machine Learning Engineer

San Francisco, CA · On-site

Machine Learning Engineer We are looking for a Machine Learning Engineer to join the growing AI and ... We value full stack ML engineers who are able to work on all parts of an ML pipeline from model ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

SynergisticIT

Full stack developer

Columbus, OH

We need data science/machine learning/data analyst and Java full stack candidates. Preferred skills for Java/full stack/devops positions include a bachelors degree or masters degree in computer ...

SynergisticIT

Full stack developer

Boise, ID

We need data science/machine learning/data analyst and Java full stack candidates. Preferred skills for Java/full stack/devops positions include a bachelors degree or masters degree in computer ...

1872 Consulting

Machine Learning Engineer

Bellevue, WA · On-site

Machine Learning Engineer - Senior Level Bellevue, WA - HQ Your Skills: * Experience with cloud ... Create a boutique "GPU-first" cloud stack optimized and focused on AI/Client workloads * Create ...

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How much do internship full stack machine learning engineer jobs pay per year?

As of Jun 3, 2026, the average yearly pay for internship full stack machine learning engineer in the United States is $134,771.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $158,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Internship Full Stack Machine Learning Engineer, and why are they important?

To succeed as an Internship Full Stack Machine Learning Engineer, you need a solid understanding of programming (Python, JavaScript), basic machine learning concepts, and foundational knowledge in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, web development tools (React, Node.js), and version control systems like Git is typically expected. Strong problem-solving abilities, collaboration skills, and a willingness to learn set exceptional interns apart. These skills enable interns to contribute effectively to both model development and deployment, bridging the gap between data science and software engineering in real-world applications.

What types of projects and responsibilities can I expect as an Internship Full Stack Machine Learning Engineer?

As an Internship Full Stack Machine Learning Engineer, you can expect to work on end-to-end machine learning projects that involve both model development and integration into web or cloud applications. This may include tasks like cleaning and preparing datasets, building and testing machine learning models, developing APIs to serve predictions, and collaborating with front-end developers to deliver user-facing features. Interns often work closely with data scientists, software engineers, and product managers, gaining exposure to the full development lifecycle. These experiences help build both technical and teamwork skills, laying a strong foundation for a future career in the field.

What is an Internship Full Stack Machine Learning Engineer?

An Internship Full Stack Machine Learning Engineer is a student or early-career professional who supports both the development of machine learning models and the integration of these models into full-stack applications. This role typically involves working on data preprocessing, building and training machine learning algorithms, and deploying these models within web or mobile applications. Interns in this field gain experience in both backend and frontend technologies, as well as in machine learning frameworks and tools. The position is ideal for those seeking hands-on experience in applying AI solutions within real-world products.

What is the difference between Internship Full Stack Machine Learning Engineer vs Software Developer Intern?

AspectInternship Full Stack Machine Learning EngineerSoftware Developer Intern
Required SkillsKnowledge of machine learning, programming (Python, JavaScript), full stack development, data handlingProficiency in programming languages (Java, Python, JavaScript), software development, basic algorithms
Work EnvironmentCollaborates on ML models, data pipelines, backend and frontend developmentFocuses on application development, coding, debugging, and testing
Industry UsageUsed in AI-driven companies, tech startups, data science teamsCommon in software firms, app development companies, tech startups

The Internship Full Stack Machine Learning Engineer role emphasizes working with machine learning models and data-driven applications, combining full stack development skills with AI expertise. In contrast, a Software Developer Intern focuses more on traditional software development tasks like coding and debugging. Both roles are valuable entry points in tech, but they target different skill sets and project types.

More about Internship Full Stack Machine Learning Engineer jobs
What cities are hiring for Internship Full Stack Machine Learning Engineer jobs? Cities with the most Internship Full Stack Machine Learning Engineer job openings:
What are the most commonly searched types of Full Stack Machine Learning Engineer jobs? The most popular types of Full Stack Machine Learning Engineer jobs are:
What states have the most Internship Full Stack Machine Learning Engineer jobs? States with the most job openings for Internship Full Stack Machine Learning Engineer jobs include:
What job categories do people searching Internship Full Stack Machine Learning Engineer jobs look for? The top searched job categories for Internship Full Stack Machine Learning Engineer jobs are:
Internship Full Stack Machine Learning Engineer jobs near you
Infographic showing various Internship Full Stack Machine Learning Engineer job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $134,771 per year, or $64.8 per hour.

Machine Learning Engineer Internship

Avride

Austin, TX • On-site

Internship

Posted 11 days ago

Job description

About Avride
Avride is a US-based developer of autonomous vehicles and delivery robots. We develop and operate both autonomous cars and delivery robots that share technologies and mutually benefit from each other's advancements-a unique approach in the industry.
About the Internship
At Avride, ML Engineer Interns operate at the intersection of cutting-edge academic research and real-world engineering. You will use our massive datasets of real driving logs to train models and develop algorithms.
During this internship, you will be embedded in our Perception team. The Perception team serves as the eyes and ears of our autonomous vehicles, transforming raw data from cameras, LiDAR, and microphones into a precise, real-time 3D understanding of the surrounding world.
You will be paired with a dedicated senior mentor and work on problems directly impacting real-world driving performance. This program is designed to give you a deep understanding of how to take a theoretical concept or novel system architecture, prototype it, and evaluate its performance within a complex, safety-critical stack.
What You'll Do
We are currently offering four different internships within our Perception Team for the Summer of 2026.
Long-Tail 3D Entity Recognition via Pre-Trained 2D Models
  • Targeted ML Investigation: Take charge of solving a classic autonomous driving challenge: long-tail entity recognition. You will research how to leverage the broad visual knowledge of pre-trained, open-source 2D models for 3D applications.
  • Simulation-Driven Evaluation: Design and run rigorous experiments in our simulation environment to prove your models can detect rare, infrequent objects without sacrificing precision.
  • Feature Integration: Work closely with your mentor to prototype and iterate on techniques that adapt these 2D features into our current perception stack.
  • Knowledge Sharing: Conclude your internship by sharing your experimental findings, recall/precision trade-offs, and simulation methodology with the research and engineering groups.

RGB-Only 3D Perception & RGB-LiDAR Fusion
  • Applied Research Ownership: Lead a scoped research initiative to advance our 3D perception capabilities. You will dive into state-of-the-art literature on RGB-only methods and formulate hypotheses to improve sensor fusion.
  • Model Training & Experimentation: Utilize Avride's extensive real-world LiDAR and camera datasets to train, test, and evaluate ML models using PyTorch, aiming to extract stronger, more reliable signals from RGB data.
  • Iterative Prototyping: Partner with your mentor to design and refine algorithms that directly enhance our existing perception baselines.
  • Knowledge Sharing: Present your methodology, fusion results, and future recommendations to the broader engineering and research teams at the end of your term.

Data Engineering - Visual Scene Search via Vector Embeddings
  • System Architecture & Design: Own the development of a new vector-based search capability to upgrade how we query our scene database. You will research and integrate embedding models (like CLIP) alongside our existing natural language systems.
  • Data Tooling Implementation: Build out the backend infrastructure using Python to map and search Avride's massive library of real-world camera data.
  • Pipeline Integration: Collaborate with your mentor to deploy these embedding models effectively, unlocking faster and smarter data mining for our labeling and perception teams.
  • Knowledge Sharing: Present your system architecture, search performance metrics, and the practical impact of your new tool to the wider engineering organization.

Audio Signal Processing & Siren Recognition Pipeline
  • End-to-End Pipeline Creation: Lead an applied engineering project centered on our vehicle microphone arrays. You will design and build a robust data mining pipeline to extract relevant audio signals from raw vehicle logs.
  • Auto-Labeling & Fine-Tuning: Leverage large open-source models to automatically label your mined data, then use that dataset to train and fine-tune a compact, efficient onboard ML model for siren recognition.
  • Edge Optimization: Partner with your mentor to iterate on the model's performance, ensuring it is highly accurate and lightweight enough for real-time onboard processing.
  • Knowledge Sharing: Wrap up your internship by demoing your automated labeling pipeline and the performance of your onboard siren detector to the engineering teams.
What You'll Need
  • Education: Currently pursuing a Bachelor's, Master's, or PhD (highly preferred) in Computer Science, Robotics, Machine Learning, Applied Mathematics, or a related field with an expected graduation date between Winter 2026 and Spring 2027.
  • Machine Learning / Math Foundation: Strong understanding of deep learning, reinforcement learning, computer vision, optimization, or probabilistic modeling.
  • Programming Skills: Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow). Basic familiarity or willingness to learn C++.
  • Research Acumen: Ability to read, understand, and implement algorithms from academic research papers. A strong analytical mindset for designing experiments and interpreting data.
  • Eagerness to Learn: Highly collaborative, open to feedback, and excited to tackle unsolved problems in the autonomous driving space.
What You'll Get
  • 1:1 Mentorship: Direct guidance from leading researchers and engineers in the autonomous vehicle industry to help you navigate technical roadblocks and grow your career.
  • Massive Compute & Data: Access to state-of-the-art driving data to fuel your experiments.
  • Networking & Culture: Invitations to tech talks, paper reading groups, intern social events, and cross-team collaborations.

Please note that this is an in-person internship based at our office in Austin, Texas. We are prioritizing candidates who currently reside within commuting distance of Austin. We do not provide relocation assistance, travel reimbursement, or housing stipends for this position.
Candidates are required to be authorized to work in the U.S. The employer is not offering relocation sponsorship, and remote work options are not available.
Avride is an equal opportunity employer and committed to providing reasonable accommodations to qualified applicants and employees with disabilities to ensure they have equal access to employment opportunities. Avride complies with the Americans with Disabilities Act (ADA), if you need a reasonable accommodation to assist with the application or hiring process, or to perform the essential functions of a job, please email jobs@avride.ai.

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