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Machine Learning Engineer Biotech Jobs in Queens, NY

Root Access Inc

Machine Learning Engineer

New York, NY · On-site

Our team is a passionate mix of engineers across electrical, firmware, software, and machine learning. Core Responsibilities * Architect Physics Foundation Models: Design and train deep learning ...

Virtu Financial

Machine Learning Engineer

New York, NY · On-site

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a small group of technologists whose primary function is building the infrastructure that powers our ...

Virtu Financial

Machine Learning Engineer

New York, NY · On-site

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a small group of technologists whose primary function is building the infrastructure that powers our ...

SageSure

Senior Machine Learning Engineer

Jersey City, NJ · On-site

$127K - $168K/yr

As a Senior Machine Learning Engineer, you'll play a crucial role in optimizing orchestration processes and ensuring fast and efficient model deployment and delivery. You'll work closely with ...

PROPRIUS

Senior Machine Learning Engineer

New York, NY

$114K - $157K/yr

Sr. Machine Learning Engineer Location: New York, NY Sponsorship: Yes Relocation: Yes Industry: Machine Learning A leading provider of AI is looking for a Sr. ML Engineer. Our client is an industry ...

Capital One

Lead Machine Learning Engineer

Manhattan, NY · On-site +1

$112K - $148K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

New York, NY · On-site

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

DraftKings

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

The Crown Is Yours As a Senior Machine Learning Engineer, you'll join a team of algorithm experts and data science technologists building innovative data products that solve analytically complex ...

Namely

Machine Learning Engineer

Manhattan, NY · On-site

$120 - $150/hr

About the role We are seeking a Machine Learning Engineer to strengthen our element classification system - working closely with data scientists and data annotators to ship and improve entity ...

New

Teleskope

Machine Learning Engineer

New York, NY · On-site

$160K - $210K/yr

About the role We are seeking a Machine Learning Engineer to strengthen our element classification system - working closely with data scientists and data annotators to ship and improve entity ...

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Showing results 41-60

All JobsMachine Learning Engineer Biotech JobsMachine Learning Engineer Biotech Jobs in Queens, NY

Machine Learning Engineer Biotech information

See Queens, NY salary details

$32.9K

$134.4K

$201.9K

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

As of Aug 8, 2026, the average yearly pay for machine learning engineer biotech in Queens, NY is $134,366.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,900.00 and $161,700.00 per year, depending on experience, location, and employer.

What does a machine learning engineer do in biotech?

A Machine Learning Engineer in biotech applies advanced algorithms and data analysis techniques to solve biological and medical problems. They work with large datasets such as genomic sequences, medical images, or clinical records to develop predictive models, automate data analysis, and uncover insights that can accelerate drug discovery, diagnostics, and personalized medicine. Their work often involves close collaboration with biologists, data scientists, and software engineers to create tools and solutions that improve healthcare outcomes. Machine Learning Engineers in this field need a strong background in both computational methods and biological sciences.

How do machine learning engineers in biotech typically collaborate with research scientists and domain experts?

Machine Learning Engineers in biotech often work closely with research scientists and domain experts to translate complex biological problems into data-driven solutions. This collaboration involves regular meetings to understand experimental data, refine project goals, and iterate on model development based on domain feedback. Engineers are expected to communicate technical concepts clearly, adapt models to fit scientific needs, and help validate results alongside laboratory teams. This interdisciplinary environment fosters innovation but also requires flexibility and strong communication skills.

What are the key skills and qualifications needed to thrive as a machine learning engineer in biotech?

To thrive as a Machine Learning Engineer in Biotech, you need a solid background in computer science, statistics, and biology, often with an advanced degree in a related field. Experience with programming languages such as Python or R, machine learning frameworks like TensorFlow or PyTorch, and familiarity with bioinformatics tools are typically required. Strong problem-solving, communication, and interdisciplinary collaboration skills set standout candidates apart. These capabilities are crucial for developing effective models that drive scientific innovation and advance biotechnological research.

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

AspectMachine Learning Engineer BiotechData Scientist Biotech
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related; knowledge of ML frameworksBachelor's or Master's in Data Science, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models, coding, deploying algorithms in biotech R&DAnalyzes biological data, interprets results, creates reports
Employer & Industry UsageBiotech firms, pharma companies, research labsBiotech companies, healthcare, research institutions

While both roles work with biological data, Machine Learning Engineers focus on developing and deploying ML algorithms, whereas Data Scientists analyze and interpret biological datasets to inform research and decision-making in biotech settings.

What are popular job titles related to Machine Learning Engineer Biotech jobs in Queens, NY? For Machine Learning Engineer Biotech jobs in Queens, NY, the most frequently searched job titles are:
What cities near Queens, NY are hiring for Machine Learning Engineer Biotech jobs? Cities near Queens, NY with the most Machine Learning Engineer Biotech job openings:
Machine Learning Engineer Biotech jobs near you
Infographic showing various Machine Learning Engineer Biotech job openings in Queens, NY as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $134,366 per year, or $64.6 per hour.

Machine Learning Engineer

Root Access Inc

New York, NY • On-site

Full-time

Re-posted 29 days ago

Job description

About the company
Root Access is a frontier electronics company. We are a NYC-based startup funded by top investors. Our team is a passionate mix of engineers across electrical, firmware, software, and machine learning.
Core Responsibilities
  • Architect Physics Foundation Models: Design and train deep learning models.
  • Build the ECAD Data Pipeline: Develop high-performance asset pipelines to convert geometric, discrete, and multi-layer PCB files (ODB++, IPC-2581, STEP, Gerber) into continuous space data.
  • Multi-Modal Architecture Integration: Collaborate on connecting upstream Graph Neural Networks (GNNs) or LLMs mapping schematic topologies to downstream spatial physics engines.
  • Optimize for Real-Time Execution: Optimize training and inference pipelines on GPU clusters.

Required Technical Skills & Qualifications
  • Education: Master's or Ph.D. in Computer Science, Mathematics, EE, Physics, or a related quantitative field with a focus on Scientific Machine Learning (SciML).
  • Deep Learning Frameworks: 4+ years of expert-level experience with PyTorch or JAX.
  • SciML Expertise: Direct, hands-on experience building and training PINNs, FNOs, etc.
  • Mathematical Depth: Exceptional understanding of partial differential equations (PDEs), vector calculus, automatic differentiation (autograd), and numerical optimization algorithms (Adam, L-BFGS).
  • Data Pipelines: Strong proficiency in manipulating spatial or geometric datasets using Python libraries (NumPy, SciPy, Shapely, Open3D, or custom voxelization matrices).

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