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Remote Full Stack Machine Learning Engineer Jobs in Secaucus, NJ

Career Renew

Senior Machine Learning Engineer

New York, NY · Remote

$165K - $225K/yr

... Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary ... stack that powers Pictor's virtual staining. The ideal candidate will have deep expertise in ...

Capital One

Sr. Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be ... Eligibility varies based on full or part-time status, exempt or non-exempt status, and management ...

Patlytics

Full Stack Engineer

Manhattan, NY · On-site +1

Invest in yourself - Professional development budget, gym membership stipend, and learning ... Hybrid work environment (open to remote pending location), while staying connected with a ...

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 ...

Mercor

Machine Learning Engineer

New York, NY · Remote

$70 - $100/hr

Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams to ... experience in Machine Learning , Data Science , Software Engineering , Computer Science ...

PLAID

Senior Machine Learning Engineer - Credit

Manhattan, NY · On-site +1

$115K - $158K/yr

We're looking for machine learning engineers with experience applying state-of-the-art machine ... You'll own AI and machine learning work across the full model lifecycle, from offline training to ...

Trunk Tools, Inc.

Senior Full Stack Engineer

New York, NY · Remote

$166K - $215K/yr

Collaborate closely with machine learning/vision engineers, LLM domain experts, and our ... remote and hybrid) 🥨 Free lunch provided in the office in NYC & Austin - you'll never go hungry ...

Trunk Tools

Senior Full Stack Engineer

New York, NY · On-site +1

$166K - $215K/yr

Collaborate closely with machine learning/vision engineers, LLM domain experts, and our ... Learning & Growth stipend Flexible long-term work options (remote and hybrid) Free lunch provided ...

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All JobsRemote Full Stack Machine Learning Engineer JobsRemote Full Stack Machine Learning Engineer Jobs in Secaucus, NJ

Remote Full Stack Machine Learning Engineer information

See Secaucus, NJ salary details

$45.2K

$137K

$193.7K

How much do remote full stack machine learning engineer jobs pay per year?

As of Jun 22, 2026, the average yearly pay for remote full stack machine learning engineer in Secaucus, NJ is $137,019.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,900.00 and $160,600.00 per year, depending on experience, location, and employer.

What is a Remote Full Stack Machine Learning Engineer?

A Remote Full Stack Machine Learning Engineer is a professional who designs, develops, and deploys machine learning solutions while working remotely. They handle both the front-end and back-end aspects of machine learning projects, including data preprocessing, model building, API development, and integration with user interfaces or cloud platforms. This role requires expertise in programming, machine learning frameworks, cloud services, and web technologies, allowing them to build end-to-end AI-driven applications from anywhere in the world.

What are some common challenges faced by remote Full Stack Machine Learning Engineers, and how can they be addressed?

Remote Full Stack Machine Learning Engineers often encounter challenges such as managing effective collaboration with cross-functional teams and ensuring smooth deployment of machine learning models into production environments. To address these, it's important to establish clear communication channels, regularly participate in virtual stand-ups, and use collaborative platforms such as GitHub and Slack. Additionally, staying organized with version control and thorough documentation helps maintain project transparency and ensures seamless handoffs between backend and frontend development. Proactively seeking feedback and scheduling regular check-ins with team members can further enhance productivity and integration within the team.

What is the difference between Remote Full Stack Machine Learning Engineer vs Remote Data Scientist?

AspectRemote Full Stack Machine Learning EngineerRemote Data Scientist
Primary FocusDeveloping end-to-end machine learning applications, including backend, frontend, and model deploymentAnalyzing data, creating models, and generating insights without necessarily building full applications
Skills RequiredProgramming (Python, JavaScript), ML frameworks, web development, deployment toolsStatistics, data analysis, visualization, Python/R, SQL
Work EnvironmentCollaborates with developers, data engineers, and product teams in tech-driven companiesWorks with data teams, analysts, and business units in various industries

While both roles involve working with data and machine learning, a Remote Full Stack Machine Learning Engineer builds complete applications with integrated ML models, whereas a Remote Data Scientist focuses on data analysis and model creation without necessarily developing full applications.

What are the key skills and qualifications needed to thrive as a Remote Full Stack Machine Learning Engineer, and why are they important?

To thrive as a Remote Full Stack Machine Learning Engineer, you need proficiency in programming languages (such as Python or JavaScript), a solid understanding of machine learning algorithms, experience with web development frameworks, and typically a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, Docker, cloud computing platforms (AWS, GCP), and version control systems (Git) is essential. Strong problem-solving skills, self-motivation, and clear communication are crucial soft skills, especially in remote and cross-functional team environments. These combined skills ensure effective design, deployment, and integration of machine learning solutions in scalable web applications while maintaining productivity in a remote setting.
What are popular job titles related to Remote Full Stack Machine Learning Engineer jobs in Secaucus, NJ? For Remote Full Stack Machine Learning Engineer jobs in Secaucus, NJ, the most frequently searched job titles are:
What job categories do people searching Remote Full Stack Machine Learning Engineer jobs in Secaucus, NJ look for? The top searched job categories for Remote Full Stack Machine Learning Engineer jobs in Secaucus, NJ are:
What cities near Secaucus, NJ are hiring for Remote Full Stack Machine Learning Engineer jobs? Cities near Secaucus, NJ with the most Remote Full Stack Machine Learning Engineer job openings:
Remote Full Stack Machine Learning Engineer jobs near you

Senior Machine Learning Engineer

Career Renew

New York, NY • Remote

$165K - $225K/yr

Full-time

Posted 2 hours ago

Job description

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus equity.
We are the leading virtual staining company revolutionizing digital pathology adoption worldwide through cutting-edge AI-powered technology. Our solutions deliver diagnostic-quality results in minutes while preserving tissue samples for comprehensive analysis.
Our breakthrough DeepStain™ and ReStain™ technologies enable unlimited virtual staining from a single tissue sample, eliminating the bottlenecks and limitations of traditional chemical staining processes. This innovation supports the critical evolution from research applications to clinical deployment, empowering laboratories to advance their digital pathology capabilities while reducing chemical waste, improving operational efficiency, and expanding diagnostic possibilities.

About the Role

We are seeking an experienced Senior ML Engineer to join our team who owns the representation-learning and generative modeling stack that powers Pictor’s virtual staining. The ideal candidate will have deep expertise in Machine Learning and building generalizable, production-ready models, and evaluations that stand up in clinical workflows.
Design and implement novel computer vision and deep learning algorithms for virtual staining and digital pathology applications
Conduct rigorous experiments to evaluate algorithm performance, validate research hypotheses, and drive iterative improvements
Develop and advance ML models leveraging Vision Transformers, Diffusion Models, GANs, and generative architectures for image-to-image translation tasks
Apply classical and learned image enhancement, denoising, and semantic segmentation techniques to histopathology imaging challenges
Explore image representation in latent space for efficient, high-fidelity virtual staining
Stay current with state-of-the-art research, identifying opportunities to apply novel techniques to PictorLabs’ product roadmap

Collaboration
Collaborate with ML Engineering and software teams to translate research prototypes into production-ready systems meeting latency and throughput requirements
Work with large-scale pathology datasets to train, validate, and fine-tune foundation models and custom architectures
Partner with software engineers, data scientists, and pathology domain experts to integrate research into production systems
Contribute to best practices for data engineering, data governance, and data quality across research and production pipelines
Leverage AI coding and ideation tools to accelerate research velocity and prototype new approaches

Required Qualifications

PhD (preferred) or Master’s degree in Computer Science, Electrical Engineering, or a related field
Deep expertise in computer vision and deep learning, with hands-on experience in one or more of: Vision Transformers, Diffusion Models, GANs, semantic segmentation, or classical image enhancement and denoising
Expert proficiency in Python and PyTorch and other scientific computing environments a plus
Strong mathematical foundation in linear algebra, probability, and optimization
Experience with large-scale model training, distributed computing, or cloud ML infrastructure (AWS, GCP, or Azure)
Knowledge of handling large scale image data, data version controls, model registry, has experience dealing with ML lifecycles
Experience with feature search, data balancing, and data curation pipelines.
Knowledge of software engineering best practices including version control (Git) and CI/CD pipelines
Excellent collaboration and communication skills, with the ability to work effectively in a fast-paced, cross-functional international startup environment
Extensive use of AI tools for coding, optimization, and ideation

Preferred Qualifications

Experience with medical imaging, digital pathology, or whole slide image (WSI) processing
Experience with LoRAs, transformer architecture and state of the art image to image translation models (Flux 2, Z-Image) and the Hugging face ecosystem
Background in generative models and fine-tuning of foundation models
Experience with GPU acceleration and optimization, including CUDA kernel engineering, TensorRT/ONNX export, and inference serving frameworks such as Triton
Experience with hosting computer vision model inference on NVIDIA DGX Spark.
Understanding of FDA regulatory requirements for AI/ML in medical devices
Experience with MLOps tools (MLflow, Kubeflow) and model versioning practices
Develop tools and frameworks to streamline ML research workflows, experimentation, and reproducibility

What We Offer

The opportunity to work on technology that directly improves patient outcomes and transforms clinical diagnostics, alongside a talented team of engineers and researchers pushing the boundaries of AI in healthcare. You will have the freedom to pursue high-impact research while seeing your work deployed at scale in real clinical environments.