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Contract Apple Machine Learning Engineer Jobs in Hoboken, NJ

ExaCare AI

Machine Learning Engineer

Manhattan, NY · On-site

$110 - $150/hr

We are seeking a highly adaptable, creative, and well‑rounded Machine Learning Engineer to join our team. You will own the end‑to‑end ML lifecycle, from dataset creation and foundational ...

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 ...

Trading Interview

Machine Learning Engineer

Manhattan, NY · On-site

$180 - $240/hr

We are looking for an engineer with robust experience in machine learning and strong mathematical foundations to join our growing ML team and to help drive the direction of our ML platform. Machine ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

We are looking for an engineer with robust experience in machine learning and strong mathematical foundations to join our growing ML team and to help drive the direction of our ML platform. Machine ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

We are looking for an engineer with robust experience in machine learning and strong mathematical foundations to join our growing ML team and to help drive the direction of our ML platform. Machine ...

Visible Hands

Machine Learning Engineer

Manhattan, NY · On-site

$150 - $190/hr

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 ...

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 ...

Root Access, Inc.

Machine Learning Engineer

Manhattan, NY · On-site

$140 - $190/hr

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 ...

Canals

Machine Learning Engineer

New York, NY · On-site

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining high quality, owning end-to-end ML pipelines while shaping product features that deliver real-world ...

Canals

Machine Learning Engineer

New York, NY · Remote

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining high quality, owning end-to-end ML pipelines while shaping product features that deliver real-world ...

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Showing results 21-40

All JobsContract Apple Machine Learning Engineer JobsContract Apple Machine Learning Engineer Jobs in Hoboken, NJ

Contract Apple Machine Learning Engineer information

See Hoboken, NJ salary details

$34.5K

$140.9K

$211.7K

How much do contract apple machine learning engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for contract apple machine learning engineer in Hoboken, NJ is $140,884.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $169,600.00 per year, depending on experience, location, and employer.

What is a contract Apple machine learning engineer?

Contract Apple Machine Learning Engineers are professionals hired on a temporary or project basis to develop and implement machine learning models and algorithms specifically for Apple’s products and platforms. They typically work on tasks such as optimizing machine learning workflows for iOS, macOS, or other Apple technologies, and may collaborate closely with Apple’s in-house teams. Their responsibilities can include data preprocessing, model training, evaluation, and integration into Apple’s ecosystem. These engineers are expected to have expertise in machine learning frameworks, programming languages like Python or Swift, and a strong understanding of Apple’s development tools. Contract roles often provide flexibility but may require quick adaptation to Apple’s proprietary systems and high standards.

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

To thrive as a Contract Apple Machine Learning Engineer, you need a strong background in computer science, mathematics, and deep learning, typically with a relevant degree and experience in building ML models. Proficiency with Python, TensorFlow or PyTorch, Apple's Core ML framework, and version control systems is commonly required. Strong problem-solving skills, collaboration, and effective communication help you navigate project requirements and work with cross-functional teams. These skills and experiences are crucial for delivering high-quality, scalable machine learning solutions that align with Apple's standards and rapidly evolving technology needs.

What are the common challenges faced by contract Apple machine learning engineers when integrating ML models into Apple’s ecosystem?

Contract Apple Machine Learning Engineers often encounter challenges such as ensuring seamless integration of machine learning models with Apple’s proprietary platforms like iOS, macOS, or Core ML. Adapting to Apple’s strict security, privacy standards, and performance requirements is essential, as is optimizing models for real-time performance on Apple devices. Collaborating effectively with cross-functional teams—such as software developers, designers, and QA engineers—is crucial to deliver scalable and user-friendly ML features within project timelines.

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Contract Apple Machine Learning Engineer jobs near you

Machine Learning Engineer

ExaCare AI

Manhattan, NY • On-site

$110 - $150/hr

Other

Re-posted 28 days ago

Job description

We are seeking a highly adaptable, creative, and well‑rounded Machine Learning Engineer to join our team. You will own the end‑to‑end ML lifecycle, from dataset creation and foundational research to building and deploying production‑grade models. If you thrive in an environment where you can quickly iterate, experiment with cutting‑edge techniques, and see your work make a tangible impact, this is the role for you.

What You'll Do
  • Novel Solution Development: Research, design, and implement novel machine learning solutions using modern architectures to tackle complex business problems.
  • Rapid Prototyping & Iteration: Build and manage efficient pipelines for rapid experimentation and hypothesis testing.
  • Experiment Tracking: Methodically design, execute, and track all experiments, including hyperparameter searches, architecture changes, and data variations, using tools like MLflow or Weights & Biases.
  • Model Deployment: Deploy models into production environments using CI/CD practices and model serving frameworks.
  • Performance Monitoring: Implement and maintain robust monitoring systems to track model performance, detect drift, and ensure reliability and scalability.
  • Advanced Model Optimization: Apply modern techniques to optimize models for inference speed, memory footprint, and cost. This includes quantization, pruning, and knowledge distillation.
  • Data Lifecycle Management: Lead efforts in dataset creation, augmentation, and curation to build high‑quality, robust training data.
  • Advanced Architectures: Stay current with and apply state‑of‑the‑art techniques, especially relating to Large Language Models (LLMs).
What You'll Bring
  • Proven experience (3+ years) in building, training, and deploying machine learning models in a production environment.
  • Expert‑level proficiency in Python.
  • Experience with modern deep learning frameworks, such as PyTorch.
  • Demonstrable experience with systematic hyperparameter searching and optimization frameworks (e.g., Optuna, Ray Tune).
  • Exceptional organizational skills, with a strong emphasis on reproducible research and methodical experiment tracking.
  • Direct experience with LLMs, including fine‑tuning, prompt engineering, RAG, and efficient inference.
  • Practical experience implementing model optimization techniques like quantization (e.g., bitsandbytes) and pruning.
  • Experience in designing and curating novel datasets from scratch.
  • Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related technical field.
Bonus Points (Preferred Qualifications)
  • Familiarity with advanced model architectures like Transformers and Mixtures of Experts (MoE).
  • Contributions to open‑source ML projects or a portfolio of personal projects demonstrating a passion for the field.
  • Strong, hands‑on understanding of the MLOps lifecycle and associated tools (e.g., Docker, Kubernetes, MLflow, Kubeflow, Prometheus).

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