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Remote Python Machine Learning Jobs in Parlin, NJ

Career Renew

Senior Machine Learning Engineer

New York, NY · Remote

$165K - $225K/yr

... remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ... Python and PyTorch and other scientific computing environments a plus Strong mathematical ...

DailyPay

Senior Machine Learning Engineer

New York, NY · Remote

$190K - $250K/yr

We are seeking a Senior Machine Learning Engineer to join our AI & ML team in New York City. You ... Proficiency in Python and experience with ML frameworks (scikit-learn, TensorFlow, PyTorch) * Solid ...

Autodesk

Senior Machine Learning Test Engineer

New York, NY · On-site +1

$120K - $157K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East ... Automate ML QA workflows using Python and CI/CD (e.g., GitHub Actions, Jenkins) * Create and ...

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How much do remote python machine learning jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for remote python machine learning in Parlin, NJ is $60.36, according to ZipRecruiter salary data. Most workers in this role earn between $49.76 and $68.56 per hour, depending on experience, location, and employer.

What is a remote Python machine learning?

A Remote Python Machine Learning job involves developing, deploying, and optimizing machine learning models using Python while working from a remote location. Responsibilities typically include data preprocessing, model training, evaluation, and integration into production systems. Professionals in this role often use frameworks like TensorFlow, PyTorch, or Scikit-learn and work with cloud platforms or on-premise infrastructure. This job requires strong programming skills, an understanding of machine learning algorithms, and experience handling large datasets. Remote positions offer flexibility but require self-discipline and effective communication with distributed teams.

What does a remote Python machine learning professional do?

A typical day in this role involves designing, developing, and testing machine learning models using Python, as well as cleaning and preprocessing large datasets. You may also spend time researching new algorithms, tuning model performance, and collaborating with data engineers, product managers, and other remote team members to integrate solutions into production. Regular code reviews, virtual meetings, and documentation are part of the workflow to ensure consistent project progress and maintain code quality. Balancing independent deep work with remote teamwork is key to succeeding in this environment.

What are the key skills and qualifications needed to thrive in remote Python machine learning?

To thrive as a Remote Python Machine Learning professional, you need a strong background in Python programming, machine learning algorithms, and data analysis, typically supported by a degree in computer science or a related field. Familiarity with libraries such as TensorFlow, PyTorch, scikit-learn, and experience using cloud platforms like AWS or Azure, as well as relevant certifications, are highly valuable. Excellent problem-solving skills, self-motivation, and clear communication are essential for remote collaboration and delivering impactful results. These capabilities enable you to tackle complex projects efficiently, drive innovation, and function effectively in distributed teams.

What are popular job titles related to Remote Python Machine Learning jobs in Parlin, NJ?

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Remote Python Machine Learning jobs near you

Senior Machine Learning Engineer

Career Renew

New York, NY • Remote

$165K - $225K/yr

Full-time

Re-posted 29 days 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.