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Machine Learning Engineer Biotech Jobs in New Jersey

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 ...

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 ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

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Machine Learning Engineer Biotech information

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 the most commonly searched types of Machine Learning Engineer Biotech jobs in New Jersey?

The most popular types of Machine Learning Engineer Biotech jobs in New Jersey are:

Infographic showing various Machine Learning Engineer Biotech job openings in New Jersey as of August 2026, with employment types broken down into 8% Internship, and 92% Full Time. Highlights an 76% In-person, 16% Hybrid, and 8% Remote job distribution.

AI / Machine Learning Engineer

Apogee Global RMS

Piscataway, NJ

Full-time

Posted 14 days ago


Job description

Apogee Global RMS is seeking an AI / Machine Learning Engineer to support our enterprise client in New Jersey. This role will focus on designing, building, and deploying advanced AI and computer vision solutions that drive innovation in identity, security, automation, and digital trust.

The ideal candidate will have strong experience developing production-grade machine learning models, working across the full ML lifecycle-from data preparation and model development to deployment and optimization across cloud and mobile environments.

Key Responsibilities:
  • Design and develop AI/ML models for computer vision, image classification, object detection, OCR, and feature extraction.
  • Build real-time image quality assessment, data processing, and intelligent capture solutions.
  • Develop and maintain data pipelines for data collection, labeling, cleaning, and augmentation.
  • Optimize ML models for cloud and mobile/on-device inference.
  • Implement fraud detection, anomaly detection, and security-focused AI capabilities.
  • Integrate ML models into production APIs and software platforms.
  • Monitor model performance and continuously improve accuracy and scalability.
  • Collaborate with engineering, product, and business teams to deliver AI-driven solutions.

Requirements

  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or related field (or equivalent experience).
  • 3+ years of experience building and deploying machine learning models in production environments.
  • Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or similar.
  • Experience with computer vision libraries (OpenCV) and OCR technologies.
  • Strong understanding of deep learning architectures for image and text recognition.
  • Experience with cloud platforms such as AWS, Azure, or GCP.
  • Strong problem-solving skills and ability to thrive in a fast-paced environment.
Preferred Qualifications:
  • Experience with model optimization and quantization for mobile deployment.
  • Knowledge of synthetic data generation and data augmentation techniques.
  • Background in fraud detection, anomaly detection, security, or identity technologies.
  • Familiarity with data privacy and compliance standards.
  • Experience contributing to open-source projects or AI research.
What You'll Do:
  • Build next-generation AI capabilities with real-world enterprise impact.
  • Work on innovative computer vision and machine learning challenges.
  • Partner with talented engineering teams to move AI solutions from research to production.
  • Drive improvements in accuracy, performance, and scalability.

Benefits

For any questions (OR) to apply, please contact us at careers@apogeeglobalrms.com.