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Machine Vision Software Engineer Jobs in New York

Software Engineer New York (On-Site) Highly Competitive Compensation + Significant Performance ... Exposure to distributed computing, large-scale analytics, or machine learning systems. * Background ...

You'll be hands-on with data, APIs, UI components, and machine learning integrations, collaborating ... and long-term architectural vision. * Stay up to date with industry trends in advertising ...

... vision, or machine learning concepts is highly desirable. • Excellent problem-solving skills and a strong analytical mindset. • Ability to work effectively in a fast-paced, collaborative team ...

Senior Software Engineer

New York, NY · On-site

$200K - $260K/yr

Job Summary As a Senior Software Engineer on the Pilots team within the Perception organization ... Adapt, refine, and integrate Machine Learning (ML) and Computer Vision (CV) models, including ...

As a Software Engineer, you will design and build core infrastructure that supports software ... machine learning, and experimental automation. Responsibilities : • Design and build core ...

About the role As a Fullstack Software Engineer, you will own meaningful parts of the product from ... Experience building AI, LLM, agent, or machine-learning products * Experience with AWS, GCP, Docker ...

About the role As a Fullstack Software Engineer, you will own meaningful parts of the product from ... Experience building AI, LLM, agent, or machine-learning products * Experience with AWS, GCP, Docker ...

Software Engineer, Machine Learning Responsibilities: * Collaborate with cross-functional teams (product, design, operations, infrastructure) to build innovative application experiences * Implement ...

Staff Software Engineer

New York, NY · On-site

$230K - $299K/yr

What the job involves As a Staff Software Engineer on the Perception team, you will be a key ... Deep expertise in one or more of: robotics, state estimation, computer vision, or applied machine ...

Showing results 21-40

Machine Vision Software Engineer information

What does a machine vision software engineer do?

A Machine Vision Software Engineer designs, develops, and maintains software systems that enable computers to interpret and process visual information from the real world. They work with cameras, sensors, and advanced algorithms to automate tasks such as inspection, identification, measurement, and guidance in industrial and robotics applications. Their responsibilities often include integrating hardware with software, optimizing image processing algorithms, and ensuring the accuracy and reliability of vision systems. These engineers play a crucial role in industries like manufacturing, automotive, healthcare, and logistics where automated visual inspection and analysis are essential.

What are some of the main challenges machine vision software engineers face when integrating vision systems into manufacturing environments?

Machine Vision Software Engineers often encounter challenges such as ensuring reliable image capture despite varying lighting conditions and accommodating different types of defects or product variations. Integrating vision systems with existing automation hardware and production lines can require close collaboration with mechanical, electrical, and process engineers. Additionally, optimizing algorithms for real-time performance while maintaining high accuracy is a frequent necessity. Continuous testing and iterative development are key to addressing these challenges and delivering robust solutions in dynamic manufacturing settings.

What are the key skills and qualifications needed to thrive as a machine vision software engineer, and why are they important?

To thrive as a Machine Vision Software Engineer, you need a solid background in computer science, image processing, and mathematics, usually backed by a relevant degree. Familiarity with programming languages such as Python or C++, machine vision libraries like OpenCV, and experience with deep learning frameworks are typically required. Strong problem-solving, attention to detail, and effective communication skills help engineers design robust solutions and collaborate with multidisciplinary teams. These competencies are crucial for developing accurate, efficient vision systems that meet real-world automation and quality control demands.

What is the difference between Machine Vision Software Engineer vs Computer Vision Engineer?

AspectMachine Vision Software EngineerComputer Vision Engineer
Required CredentialsBachelor's or Master's in CS, EE, or related; experience with image processingBachelor's or Master's in CS, EE, or related; strong programming skills in Python, C++
Work EnvironmentManufacturing, robotics, quality inspectionAutonomous vehicles, AI research, multimedia applications
Industry UsageManufacturing, industrial automation, roboticsTech, automotive, research institutions
Search & Comparison IntentFocus on industrial and automation applicationsFocus on AI, perception, and multimedia systems

While both roles involve image analysis and programming skills, Machine Vision Software Engineers primarily work on industrial automation and manufacturing systems, whereas Computer Vision Engineers focus on AI-driven perception in autonomous vehicles, robotics, and multimedia applications. The roles overlap in skills but differ in application environments and industry focus.

What job categories do people searching Machine Vision Software Engineer jobs in New York look for?

The top searched job categories for Machine Vision Software Engineer jobs in New York are:

What cities in New York are hiring for Machine Vision Software Engineer jobs?

Cities in New York with the most Machine Vision Software Engineer job openings:

Infographic showing various Machine Vision Software Engineer job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 16% Part Time, and 5% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution.

Software Engineer, Machine Lifecycle

Tower Research Capital

New York, NY • On-site

Full-time

PTO

Posted 3 days ago

New


Job description

Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities.
Tower is home to some of the world's best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization. 

Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance.

At Tower, every employee plays a role in our success. Our Business Support teams are essential to building and maintaining the platform that powers everything we do - combining market access, data, compute, and research infrastructure with risk management, compliance, and a full suite of business services. Our Business Support teams enable our trading and engineering teams to perform at their best.

At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential.

Summary:
This role owns the journey of every machine in our fleet: from the moment a server is racked, cabled, and powered on, to the moment it is fully configured, validated, and available for users. Your mission is to make that journey zero-touch.

You will design and build the automation pipeline that takes a machine through discovery, firmware and BIOS configuration, OS installation, configuration management, health validation and burn-in, and finally handoff into production, treating each stage as code that lives in Git, runs through CI/CD, and can be reviewed, tested, and rolled back like any other software.

The guiding principle is GitOps for physical infrastructure: the desired state of the fleet is declared in a repository, and automation continuously reconciles reality against it. A new machine shows up as a commit; a decommission is a deletion; drift is detected and corrected by the pipeline, not by a person with a checklist.


Responsibilities:

  • Design and build the end-to-end machine lifecycle pipeline: from power-on and network boot through OS install, configuration, validation, and production handoff.
  • Automate hardware bring-up via out-of-band management (BMC, Redfish, IPMI): firmware updates, BIOS settings, boot order, and inventory discovery.
  • Automate OS provisioning with network boot (PXE / UEFI HTTP boot) and unattended installation, so no one ever installs a machine by hand.
  • Write and maintain the Ansible and Python that configure machines into their final roles, replacing manual runbooks with reviewed, versioned code.
  • Apply GitOps and CI/CD principles to the fleet: desired state in Git, changes through merge requests, pipelines that test and apply them, and reconciliation that catches drift.
  • Build automated validation and burn-in: health checks, stress tests, and acceptance criteria a machine must pass before users ever see it.
  • Model the lifecycle as a state machine (new, provisioning, validating, in-service, needs-repair, decommissioned) with clear, automated transitions and an auditable history.
  • Instrument the pipeline with metrics and logging so we always know where a machine is in its lifecycle, and where the process is slow or failing.
  • Work with the HPC and datacenter teams to fold their hard-won operational knowledge into the automation, one stage at a time.

Qualifications:

  • A smart, curious engineer who learns fast and is genuinely excited by the challenge of automating physical infrastructure end to end. This matters more to us than any specific line on your resume.
  • Strong Python for building automation, tooling, and services, not just scripts.
  • Hands-on Ansible experience: writing playbooks and roles you would be happy to code-review, not just run.
  • A solid grasp of CI/CD principles: pipelines, testing, staged rollouts, and the discipline of driving change through version control.
  • An automation-first, GitOps mindset: you believe infrastructure state belongs in Git, and that any task done by hand twice should be code.
  • Working knowledge of Linux: comfortable with the boot process, system services, and debugging when a machine does not come up the way it should. Depth here is a real plus, but interest and trajectory count.
  • Sound engineering judgment: you design workflows that fail safely, retry sensibly, and leave an audit trail.
  • Clear communication and the patience to turn tribal operational knowledge into reliable, documented automation.

Nice to Have:

  • Experience with bare-metal provisioning tooling such as MAAS, Tinkerbell, Foreman, Ironic, or a home-grown equivalent.
  • Familiarity with out-of-band management: BMCs, Redfish, IPMI, and vendor variants like iDRAC or iLO.
  • Exposure to hardware validation and burn-in: stress testing, firmware qualification, or failure prediction at fleet scale.
  • Experience with GitOps tooling or declarative infrastructure management in general.
  • Prior work in datacenter, HPC, or large-fleet environments where machines number in the hundreds or thousands.


Anticipated annual base salary range $150,000-$250,000, plus eligible for discretionary bonus.

Tower's headquarters are in the historic Equitable Building, right in the heart of NYC's Financial District and our impact is global, with over a dozen offices around the world.

 At Tower, we believe work should be both challenging and enjoyable. That is why we foster a culture where smart, driven people thrive - without the egos. Our open concept workplace, casual dress code, and well-stocked kitchens reflect the value we place on a friendly, collaborative environment where everyone is respected, and great ideas win.

Our benefits include:

  • Generous paid time off policies
  • Savings plans and other financial wellness tools available in each region
  • Hybrid working opportunities
  • Free breakfast, lunch, and snacks daily
  • In-office wellness experiences and reimbursement for select wellness expenses (e.g., gym, personal training and more)
  • Company-sponsored sports teams and fitness events (JPM Corporate Challenge, Cycle for Survival, Wall Street Rides FAR and more)
  • Volunteer opportunities and charitable giving
  • Social events, happy hours, treats, and celebrations throughout the year
  • Workshops and continuous learning opportunities

At Tower, you'll find a collaborative and welcoming culture, a diverse team and a workplace that values both performance and enjoyment. No unnecessary hierarchy. No ego. Just great people doing great work - together.

Tower Research Capital is an equal opportunity employer.