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Sr Machine Learning Engineer Jobs in Hackensack, 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 ...

Digitalturbine

Senior Machine Learning Engineer

New York, NY · On-site +1

$114K - $157K/yr

As a Senior Machine Learning Engineer, you'll design and scale the ML systems behind ad ranking, bid optimization, recommendation, and user-level prediction across our demand and supply businesses ...

New

KARGO

Senior Machine Learning Engineer

New York, NY

$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 ...

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 ...

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 ...

Kargo

Senior Machine Learning Engineer

Manhattan, 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 ...

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 ...

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 ... Engineer agentic systems. Develop planning, retrieval, tool-use, and orchestration components for ...

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Showing results 41-60

All JobsSr Machine Learning Engineer JobsSr Machine Learning Engineer Jobs in Hackensack, NJ

Sr Machine Learning Engineer information

See Hackensack, NJ salary details

$64.9K

$138K

$200.1K

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

As of Aug 16, 2026, the average yearly pay for sr machine learning engineer in Hackensack, NJ is $138,029.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,000.00 and $156,500.00 per year, depending on experience, location, and employer.

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

AspectSr Machine Learning EngineerData Scientist
CredentialsBachelor's/Master's in CS, ML, or related fields; experience with ML frameworksBachelor's/Master's/PhD in CS, Statistics, or related fields; strong analytical skills
Work EnvironmentDevelops and deploys ML models, collaborates with engineering teamsAnalyzes data, builds models, interprets data insights for business
Industry UsageTech, finance, healthcare, e-commerceResearch, marketing, finance, tech

While both roles involve working with data and models, Sr Machine Learning Engineers focus on building and deploying scalable ML systems, whereas Data Scientists primarily analyze data and develop insights. The roles often overlap but differ in technical focus and responsibilities.

How does a Sr Machine Learning Engineer typically collaborate with data scientists and software engineers within a project team?

Sr Machine Learning Engineers frequently act as a bridge between data scientists, who focus on model development and experimentation, and software engineers, who handle system integration and production deployment. They translate prototype models into scalable, production-ready solutions, ensuring that models are optimized for real-world performance. Collaboration often involves reviewing code, aligning on data pipeline requirements, and participating in regular team meetings to address technical and business objectives. This cross-functional teamwork is essential for delivering reliable machine learning products.

What is a Sr Machine Learning Engineer?

Senior Machine Learning Engineers are experienced professionals who design, develop, and implement machine learning models and systems. They work on complex problems, lead technical projects, and often mentor junior engineers. Their responsibilities include data preprocessing, model selection, algorithm development, and optimizing solutions for scalability and performance. Senior ML Engineers also collaborate closely with data scientists, software engineers, and stakeholders to integrate machine learning into products and services.

What are the key skills and qualifications needed to thrive as a Sr Machine Learning Engineer?

To thrive as a Sr Machine Learning Engineer, you need advanced expertise in machine learning theory, programming (Python, R), data modeling, and a strong background in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, cloud platforms (AWS, GCP), and relevant certifications (like TensorFlow Developer) is highly beneficial. Strong problem-solving skills, effective communication, and the ability to lead and mentor teams set top candidates apart. These skills ensure the ability to design scalable ML solutions, collaborate effectively, and drive impactful business outcomes.

What are popular job titles related to Sr Machine Learning Engineer jobs in Hackensack, NJ?

For Sr Machine Learning Engineer jobs in Hackensack, NJ, the most frequently searched job titles are:

What job categories do people searching Sr Machine Learning Engineer jobs in Hackensack, NJ look for?

The top searched job categories for Sr Machine Learning Engineer jobs in Hackensack, NJ are:

What cities near Hackensack, NJ are hiring for Sr Machine Learning Engineer jobs?

Cities near Hackensack, NJ with the most Sr Machine Learning Engineer job openings:

Sr Machine Learning Engineer jobs near you
Infographic showing various Sr Machine Learning Engineer job openings in Hackensack, NJ as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $138,029 per year, or $66.4 per hour.

Senior Machine Learning Engineer

Thalo Labs

New York, NY • On-site

$150K - $180K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 24 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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