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Home Based Vision Engineer Jobs in California (NOW HIRING)

Mill

Software Engineer, AI/Computer Vision

San Bruno, CA · On-site

$250K/yr

We build smart systems and infrastructure for homes, businesses, and municipalities that transform ... About the Role We're hiring a Computer Vision Engineer to work on the CV technology behind Mill ...

Pano

Senior AI/Computer Vision Engineer

San Francisco, CA · On-site +1

$195K - $255K/yr

The Role We are building the next generation of cloud/edge-based vision systems that combine ... As a Senior AI/Computer Vision Engineer, you will lead the design, development, optimization, and ...

Archer

Computer Vision Engineer

San Jose, CA · On-site

$140K - $260K/yr

This role must be based onsite in the United States. Visa sponsorship is not available for this ... Design and implement deep-learning and classical computer vision algorithms for real-time, embedded ...

Cesna Group

Computer Vision R&D Engineer

San Diego, CA · On-site

$100K - $200K/yr

... stack machine vision/image-based and machine learning solutions, using C++ and Python ... least of the programming language C++ / Python / CUDA * Have at least one of the followings ...

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All JobsHome Based Vision Engineer JobsHome Based Vision Engineer Jobs in California

Home Based Vision Engineer information

What is the difference between Home Based Vision Engineer vs Remote Vision Specialist?

AspectHome Based Vision EngineerRemote Vision Specialist
Required CredentialsBachelor's in Vision Science or related field, certifications in ophthalmic technologySimilar certifications, often with additional focus on telehealth tools
Work EnvironmentHome office setup, often with client or lab interactionPrimarily remote, using telecommunication tools, minimal in-person contact
Employer & Industry UsageOptometry clinics, vision care companies, telehealth providersTelehealth platforms, vision care companies, remote diagnostics services

Both roles involve remote work with a focus on vision-related tasks, but Home Based Vision Engineers often have more hands-on equipment interaction, while Remote Vision Specialists focus on remote diagnostics and consultations. The choice depends on the specific job responsibilities and required certifications.

What are the most commonly searched types of Vision Engineer jobs in California?

The most popular types of Vision Engineer jobs in California are:

What cities in California are hiring for Home Based Vision Engineer jobs?

Cities in California with the most Home Based Vision Engineer job openings:

Home Based Vision Engineer jobs near you

Software Engineer, AI/Computer Vision

San Bruno, CA • On-site

Mill
1 - 10 employees
Learn more about Millexternal

$250K/yr

Full-time

Re-posted just now

Job description

Mill is a waste prevention technology company reimagining what it means to eliminate waste, starting with food. We build smart systems and infrastructure for homes, businesses, and municipalities that transform food scraps from landfill-bound waste into valuable resources, including chicken feed. Tens of thousands of Mill's residential food recyclers are already helping households divert millions of pounds of food scraps every year, paving the way for our upcoming launch of Mill Commercial-the industry's first end-to-end solution for managing, understanding, and preventing food waste in commercial environments (e.g. grocery, restaurants, food services). At Mill, we are passionate about building easy-to-use, beautifully designed technologies that keep food in the food system and out of landfills.
About the Role
We're hiring a Computer Vision Engineer to work on the CV technology behind Mill Commercial - the computer vision and agentic systems that turn a stream of food waste into operational intelligence for commercial kitchens. Mill Commercial integrates a camera into our high-capacity food recycler; models identify and quantify food scraps, and our pipeline turns that signal into procurement and operational guidance for large food service operators.
You'll join a small, capable team, owning the modeling and training infrastructure that powers our CV technology. You will design the cloud-side evaluation harness to determine if edge models meet production targets and build the ground-truth workflows to support them. This is a hands-on IC role for someone who brings deep computer vision fundamentals to fine-tuning models, building MLOps pipelines, and establishing a methodical approach to managing system complexity.
What You'll Do
  • Train and evaluate segmentation, classification, and mass-estimation models for the Mill Commercial camera pipeline - from prompting foundation models to fine-tuning ConvNets and VLMs.
  • Optimize edge models for production performance, and operationalize and scale the ML pipeline with model lineage tracking end to end.
  • Create and curate datasets per customer/vertical - more customized, purpose-driven data - to support accuracy targets across food types, kitchen environments, and deployment configurations.
  • Analyze failure cases systematically - unfamiliar food classes, novel kitchen environments, challenging lighting and clutter conditions - and drive the data and modeling decisions that close accuracy gaps.
  • Build annotation tooling and ground-truth generation workflows, including foundation-model-assisted labeling, to keep pace with model iteration.
  • Bring a methodical approach and strong opinions, backed by experience, to the modeling and evaluation decisions you own - and partner with the team's MLOps and edge engineers on training practices, versioning, and deployment tradeoffs as they come up.
What We're Looking For
  • Strong fundamentals in computer vision and deep learning - segmentation, detection, classification, tracking - deep enough to make informed architecture calls.
  • Fluency with modern ML approaches - VLMs, LLMs, foundation models, and agentic systems - alongside classical deep learning. You know when to fine-tune a ConvNet, when to prompt a VLM, and when to wire up an agent, and you understand the practical realities of putting any of them into a product.
  • Experience evaluating ML models rigorously - designing metrics, building eval harnesses, and using results to drive product decisions rather than just publish a number.
  • Product shipping experience - you've taken a model to production and dealt with what comes after (drift, edge cases, latency budgets), not just to a benchmark.
  • Bias for action - you'd rather ship a good-enough experiment and learn from it than wait for the perfect plan.
  • Experience making build-vs-buy or tooling decisions backed by data or a clear rubric, not just instinct - you can show your work on how you got there.
  • Clear, direct communication - you can explain tradeoffs to non-technical stakeholders, push back honestly when you disagree, and write docs that others can follow.
  • Genuine interest in applying AI to food waste reduction and sustainability. This is a mission-driven product and we want people who care about the mission.
  • Software skills: Python, PyTorch, OpenCV. Experience with LLM and agent frameworks.
Nice to Have
  • Experience with video understanding (temporal consistency, tracking, video segmentation)
  • Experience with MLOps tooling (Weights & Biases, MLflow, SageMaker, ClearML, or equivalents)
  • Hardware / IoT product experience, particularly with computer vision and cameras for embedded systems

The estimated base salary range for this position is $220-250K, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs. At Mill, it is not typical for an individual to be hired at or near the top of the range for their role.

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