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Senior Machine Learning Engineer Jobs in Bound Brook, NJ

Thalo Labs

Senior Machine Learning Engineer

New York, NY · On-site

$150K - $180K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

As our Senior Machine Learning Engineer, you'll own the intelligence layer of Thalo's platform. We generate hundreds of gigabytes of HVAC sensor data no one in the world has seen before, and your job ...

KARGO

Senior Machine Learning Engineer

New York, NY · On-site

$150K - $175K/yr

The Opportunity Kargo is hiring a senior machine learning engineer to own the evolution of Finetouch, our creative scoring system--leading the design and production deployment of multimodal ML models ...

Kargo

Senior Machine Learning Engineer

New York, NY · On-site

$150K - $175K/yr

The Opportunity Kargo is hiring a senior machine learning engineer to own the evolution of Finetouch, our creative scoring system-leading the design and production deployment of multimodal ML models ...

Alt

Senior Machine Learning Engineer

New York, NY · On-site +1

$114K - $157K/yr

We're hiring a Senior Machine Learning Engineer who thrives on owning models end-to-end, from research through production. In this role, you'll own productization of Alt's pricing and underwriting ...

Forhyre

Machine Learning Engineer

New York, NY

We are looking for a Machine Learning Engineer to help us create artificial intelligence products. Machine Learning Engineer responsibilities include creating machine learning models and retraining ...

Quantiphi, Inc.

Senior Machine Learning Engineer

New York, NY · On-site +1

$134K - $176K/yr

... learning and growth. If working in an environment that encourages you to innovate and excel, not ... Engineer agentic systems. Develop planning, retrieval, tool-use, and orchestration components for ...

Zencastr

Senior Machine Learning Engineer (Remote)

New York, NY · On-site +1

$114K - $157K/yr

We are looking for an outstanding machine learning engineer to join our team! The role will provide an opportunity to work on large scale machine learning to improve the podcast creation experience ...

Quantiphi, Inc.

Senior Machine Learning Engineer

New York, NY · On-site +1

$134K - $176K/yr

... learning and growth. If working in an environment that encourages you to innovate and excel, not ... Quantiphi is an award-winning, AI-First global digital engineering company that helps the world ...

SeatGeek

Senior Machine Learning Engineer

New York, NY · On-site +1

$145K - $209K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We are looking for Software Engineers with varying levels of experience to join SeatGeek's R&D team ... learning from others Our stack You do not need experience with all of these, but we thought you ...

SeatGeek

Senior Machine Learning Engineer

New York, NY · On-site

$145K - $209K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We are looking for Software Engineers with varying levels of experience to join SeatGeek's R&D team ... learning from others Our stack You do not need experience with all of these, but we thought you ...

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Showing results 21-40

All JobsMachine Learning Engineer JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in Bound Brook, NJ

Senior Machine Learning Engineer information

See Bound Brook, NJ salary details

$63.4K

$134.8K

$195.5K

How much do senior machine learning engineer jobs pay per year?

As of Aug 18, 2026, the average yearly pay for senior machine learning engineer in Bound Brook, NJ is $134,840.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,300.00 and $152,900.00 per year, depending on experience, location, and employer.

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

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

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

What is the difference between Senior Machine Learning Engineer vs Data Scientist?

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What cities near Bound Brook, NJ are hiring for Senior Machine Learning Engineer jobs?

Cities near Bound Brook, NJ with the most Senior Machine Learning Engineer job openings:

Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in Bound Brook, NJ as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $134,840 per year, or $64.8 per hour.

Senior Machine Learning Engineer

Thalo Labs

New York, NY • On-site

$150K - $180K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 26 days ago

Job description

Who We Are:
The world is electrifying, and HVAC is at the center of it. Over the next decade, 100 to 200 million new heat pumps and HVAC units will become the backbone of a decarbonized world, but the industry has no way to keep them running well. The technician workforce has barely grown while the equipment base has multiplied, reactive repairs eat most of a tech's time, and half the installed base gets no real maintenance at all, wasting energy and driving billions in emergency costs. Thalo is fixing this. We're building the physical AI layer for HVAC: sensors plus physics-based intelligence that turn static equipment into self-monitoring systems and shift service from guesswork to data. Every sensor we deploy makes the platform smarter and builds a dataset on how equipment truly performs that no one else can.
We're a small team that has built self-driving cars at Waymo, worked on satellite imagery at Google, designed systems for John Deere, developed space missions for NASA, and led manufacturing design for Boom Supersonic jets. Now we're bringing that same rigor to one of the most important buildouts of our lifetime. In this role, the models you build decide whether a technician is sent to the right unit at the right time, and whether a building wastes energy or runs clean. It's a rare chance to work on a generational climate challenge, with first-of-its-kind data and a team of high performers who ship.
About the Role:
As our Senior Machine Learning Engineer, you'll own the intelligence layer of Thalo's platform. We generate hundreds of gigabytes of HVAC sensor data no one in the world has seen before, and your job is to turn it into the detection algorithms, physics-based models, and product features that tell our customers exactly what's wrong with their equipment and what to do about it.
This is a hands-on, end-to-end role for someone who wants to own a problem from raw time-series data all the way to a shipped, customer-facing feature. You'll build and tune our issue-detection engine, put physics-based, ML, and LLM-powered models into production, establish how we evaluate and trust them, and work closely with our engineering, customer success, and business development teams to make sure the intelligence we ship is accurate, trustworthy, and genuinely useful in the field. You'll be a senior voice on a small, mighty team!
What we offer:
  • An immediate opportunity to make an impact fighting climate change with a mission-driven team.
  • An in-person, collaborative culture. In our midtown Manhattan office, we not only have a stocked pantry but we also dedicate time to connect with each other during weekly happy hours and quarterly offsites.
  • National subsidized healthcare plans for medical, dental, and vision insurance.
  • Additional benefits include a 401(k) program, 12 weeks paid parental leave, and paid time off.
  • Free mental health and professional coaching appointments through Lyra.
  • At our ground-floor stage, our compensation structure places a strong emphasis on the value of high equity, with an annual compensation ranging from $150,000-$180,000.

What you'll do:
  • Own, extend, and improve Thalo's issue-detection engine spanning the electrical, refrigerant, and equipment-performance diagnostics at the core of our product
  • Research, develop, and implement ML, statistical, and LLM-based models in production, working directly with first-of-its-kind streaming sensor time-series data
  • Own our AI-evaluation practice: build labeled fault sets (from service outcomes, physics-vs-LLM disagreements, and field cross-checks), define accuracy metrics, and stand up an eval harness that regression-tests every prompt change, new detector, and model upgrade before it ships
  • Turn model outputs into clear, actionable insights and reports our field, CS, and BD teams can confidently put in front of customers
  • Continuously improve the data pipeline for large-scale ingestion, storage, transformation, and analysis so detection runs reliably and cost effectively as we scale
  • Partner closely with hardware, software, and business teams to connect field and customer insights back into the product and document your work so the whole team can build on it

What you have:
  • 5+ years building and deploying ML or statistical models on production data, ideally in an early-stage startup environment
  • M.S. or higher in a quantitative discipline such as math, physics, statistics, or data science (or equivalent applied experience)
  • Strong applied experience with time-series or streaming sensor data, including anomaly detection, forecasting, signal processing, or similar
  • Hands-on experience shipping production features on frontier LLMs (e.g., prompt engineering, structured output, tool-use/agents, and RAG) with the judgment to know when an LLM is the right tool versus a deterministic rule or a statistical model
  • Experience evaluating AI systems: building eval sets, measuring precision/recall, using LLM-as-judge, and guarding against regressions as prompts and models change
  • Fluency in Python and the modern data stack, with the software-engineering chops to ship production-grade code (not just notebooks)
  • A real customer instinct: the ability to translate a model output into a plain-English insight a technician or building operator will trust and act on
  • Curiosity about the physical world and the drive to understand the "why" behind the product, not just how to implement it
  • A self-directed, ownership mindset and a habit of documenting and sharing context

Bonus points:
  • A passion for tackling climate change and promoting sustainability
  • HVAC, refrigeration, combustion, building-systems, or energy-domain experience (a strong plus, but something we're happy to help the right person learn)
  • Experience with agentic / tool-use systems, RAG over technical documentation, or LLM vision
  • Familiarity with LLM cost/latency optimization (prompt caching, batch inference) and model governance (managing upgrades, monitoring output/score drift, A/B-testing context changes)
  • Frontier-class LLM, open source LLM, and/or AWS Bedrock in production
  • Full-stack comfort to take a feature to the UI (React/TypeScript); time-series databases (InfluxDB, TimescaleDB) and tools like Grafana; a degree in a quantitative or engineering discipline

$150,000 - $180,000 a year
Commitment to Diversity, Equity, and Inclusion:
Thalo Labs is committed to diversity and building an equitable and inclusive environment for people of all backgrounds and experiences. We think that a diverse team is critical to Thalo's success. We especially encourage members of traditionally underrepresented communities to apply, including women, people of color, LGBTQ+ people, veterans, and people with disabilities.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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