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Embedded Machine Learning Internship Jobs in Berkeley, CA

Sesame

Data Engineer, Machine Learning

San Francisco, CA · On-site

$170K - $260K/yr

You'll collaborate directly with machine learning engineers and researchers - your job is to make ... You'll be deeply embedded with ML teams, understanding their workflows and building infrastructure ...

Sesame

Data Engineer, Machine Learning

San Francisco, CA · On-site

$120 - $160/hr

You'll collaborate directly with machine learning engineers and researchers -- your job is to make ... You'll be deeply embedded with ML teams, understanding their workflows and building infrastructure ...

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Embedded Machine Learning Internship information

See Berkeley, CA salary details

$31.2K

$52.1K

$107.8K

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

As of Aug 18, 2026, the average yearly pay for embedded machine learning internship in Berkeley, CA is $52,141.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,800.00 and $56,300.00 per year, depending on experience, location, and employer.

What is an embedded machine learning internship?

An Embedded Machine Learning Internship is a temporary position designed for students or recent graduates to gain hands-on experience in developing and deploying machine learning algorithms on embedded systems. These internships typically involve working with hardware such as microcontrollers, sensors, or edge devices, and using specialized tools to optimize machine learning models for low-power and resource-constrained environments. Interns collaborate with engineers and data scientists to create efficient, real-world AI solutions that run directly on devices rather than relying on cloud computing. This role helps bridge the gap between theoretical machine learning concepts and practical implementation on embedded platforms.

What are some typical projects or tasks I might work on during an embedded machine learning internship?

During an Embedded Machine Learning Internship, you can expect to work on projects such as optimizing machine learning models to run efficiently on hardware with limited resources, integrating AI algorithms into embedded systems (like microcontrollers or IoT devices), and performing real-time data processing. You'll likely collaborate closely with software engineers and hardware designers to test models on physical devices, debug performance issues, and contribute to documentation. These experiences provide practical exposure to the challenges of deploying AI in real-world, resource-constrained environments and help build skills valuable for a future career in embedded AI.

What are the key skills and qualifications needed to thrive as an embedded machine learning intern, and why are they important?

To thrive as an Embedded Machine Learning Intern, you need a background in computer science, electrical engineering, or a related field with strong programming skills in C/C++ and Python, as well as foundational knowledge of machine learning algorithms. Experience with embedded systems development tools (such as ARM Cortex, Raspberry Pi, or Arduino), version control systems, and familiarity with ML frameworks like TensorFlow Lite or Edge Impulse is often required. Analytical thinking, problem-solving ability, and effective teamwork are vital soft skills for success in this role. These skills and qualities are crucial for efficiently developing, optimizing, and deploying machine learning solutions on resource-constrained embedded platforms.

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Embedded Machine Learning Internship jobs near you

Data Engineer, Machine Learning

Sesame

San Francisco, CA • On-site

$170K - $260K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 2 days ago

Job description

About Sesame
Sesame believes in a future where computers are lifelike - with the ability to see, hear, and collaborate with us in ways that feel natural and human. With this vision, we're designing a new kind of computer, focused on making voice agents part of our daily lives. Our team brings together founders from Oculus and Ubiquity6, alongside proven leaders from Meta, Google, and Apple, with deep expertise spanning hardware and software. Join us in shaping a future where computers truly come alive.
About the Role
We're looking for a Data Engineer to build and maintain the data pipelines that feed Sesame's AI models. You'll collaborate directly with machine learning engineers and researchers - your job is to make sure they have the right data, in the right shape, at the right time to train, evaluate, and ship models.
Sesame's data is rich and complex: conversations, voice, sensor signals, and product telemetry. You'll design the systems that take raw, unstructured, multimodal data and turn it into clean, versioned, well-documented datasets that ML teams can trust and build on confidently.
This is a deeply technical, infrastructure-focused role - closer to ML engineering than traditional data analytics. You'll be deeply embedded with ML teams, understanding their workflows and building infrastructure that accelerates the full model development lifecycle - from data collection and labeling through training and evaluation.
Responsibilities
  • Design and build production data pipelines that prepare conversational, voice, and multimodal data for model training and evaluation.
  • Partner directly with ML engineers to understand data requirements for new models and experiments, and deliver datasets that meet those needs.
  • Build and maintain infrastructure for dataset versioning, lineage tracking, and reproducibility - so any training run can be traced back to its exact data.
  • Develop data quality frameworks that catch issues before they become model quality issues: schema validation, drift detection, and coverage monitoring.
  • Optimise large-scale data processing for cost and performance across Sesame's cloud infrastructure.
  • Build tooling that makes it easy for ML engineers and researchers to discover, explore, and request data independently.
  • Define and enforce data governance and privacy standards, particularly around sensitive conversational and voice data.
  • Contribute to architecture decisions around Sesame's broader data platform as the team and data volume grow.

Required Qualifications:
  • 5+ years in data engineering, with meaningful experience supporting ML or AI teams specifically.
  • Strong SQL and Python skills - you'll use both daily.
  • Experience building and operating ETL/ELT pipelines at scale using modern data platforms and tooling.
  • Experience with workflow orchestration systems such as Airflow, Dagster, or Prefect.
  • Hands-on experience with ML data workflows: training data pipelines, dataset versioning, data labeling pipelines, or model evaluation data.
  • A solid understanding of how ML teams work - you don't need to train models; what matters is understanding what makes a good training dataset and why data quality directly affects model performance.
  • Comfort working with unstructured and semi-structured data - audio, text, JSON logs - not just clean relational tables.
  • Strong communication skills. You'll be embedded with ML engineers and need to bridge data systems and model requirements effectively.
Preferred Qualifications:
  • Vector databases, embedding storage, or feature stores.
  • Data from hardware or embedded systems: telemetry, sensors, real-time streams.
  • Distributed compute frameworks for large-scale data processing such as Ray or Spark.
  • Kubernetes and managed Kubernetes environments such as GKE or EKS.
  • Data privacy frameworks, especially around voice or conversational data.
  • Building internal tooling or self-serve data platforms.

Sesame is committed to a workplace where everyone feels valued, respected, and empowered. We welcome all qualified applicants, embracing diversity in race, gender, identity, orientation, ability, and more. We provide reasonable accommodations for applicants with disabilities. Contact careers@sesame.com for assistance.
Full-time Employee Benefits:
  • 401 (k) max employer match: 3.5% of compensation
  • 100% employer-paid health, vision, and dental benefits for you and your dependents
  • Unlimited PTO and sick time
  • Flexible spending account with employer matching up to $1,650/year (medical FSA)
  • Guardian Employee Assistance Program (EAP)
  • Opportunity to share in the company's success with competitive stock options

Benefits do not apply to contingent/contract workers.

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