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Junior Machine Learning Engineer Jobs in Hackensack, NJ

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 ...

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 ...

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 ...

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 ...

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 ...

New

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 ...

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 ...

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 ...

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 ...

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 ...

Machine Learning Engineer

New York, NY · On-site +1

$209K - $250K/yr

Machine Learning Engineer Location: 55 Water Street, New York, NY 10041 (Telecommuting permitted within normal commuting distance of New York, NY office) Job Duties: Kensho Technologies LLC seeks a ...

Lead Machine Learning Engineer (IC)

New York, NY · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer (IC) 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.

Lead Machine Learning Engineer (IC)

New York, NY · On-site

$112K - $147K/yr

Lead Machine Learning Engineer (IC) 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.

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 ...

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 ...

As a Machine Learning Engineer at WireScreen, you will be working across our data systems to unlock the source of truth behind one of the world's economic powerhouses: China. This role is critical to ...

Machine Learning Engineer @ Clay Clays ambition is to build a self-learning revenue engine : a product that gets smarter every time someone uses it. This means data, ML, and AI are at the heart of ...

Showing results 21-40

Junior Machine Learning Engineer information

See Hackensack, NJ salary details

$36.5K

$78.3K

$119.4K

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

As of Aug 18, 2026, the average yearly pay for junior machine learning engineer in Hackensack, NJ is $78,308.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,900.00 and $87,300.00 per year, depending on experience, location, and employer.

What does a junior machine learning engineer do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

What kinds of projects and responsibilities can a junior machine learning engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

What are the key skills and qualifications needed to thrive as a junior machine learning engineer, and why are they important?

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

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

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

How much do junior machine learning engineers make?

Junior machine learning engineers typically earn between $70,000 and $100,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.

What are the most commonly searched types of Machine Learning Engineer jobs in Hackensack, NJ?

The most popular types of Machine Learning Engineer jobs in Hackensack, NJ are:

What are popular job titles related to Junior Machine Learning Engineer jobs in Hackensack, NJ?

For Junior Machine Learning Engineer jobs in Hackensack, NJ, the most frequently searched job titles are:

What job categories do people searching Junior Machine Learning Engineer jobs in Hackensack, NJ look for?

The top searched job categories for Junior Machine Learning Engineer jobs in Hackensack, NJ are:

What cities near Hackensack, NJ are hiring for Junior Machine Learning Engineer jobs?

Cities near Hackensack, NJ with the most Junior Machine Learning Engineer job openings:

Infographic showing various Junior Machine Learning Engineer job openings in Hackensack, NJ as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 26% Part Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $78,308 per year, or $37.6 per hour.

Sr. Machine Learning Engineer

Canoe Intelligence

Manhattan, NY • On-site

$180 - $220/hr

Other

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

COMPANY: Canoe Intelligence

WEBSITE: https://canoeintelligence.com/

TITLE: Sr. Machine Learning Engineer

LOCATION: New York City or London (hybrid) / Fully Remote in the United States or United Kingdom

SALARY: $180,000 - $220,000 (based on NYC, will be adjusted for geo)

The Role

We are looking for a Senior Machine Learning Engineer to design and deploy models that make sense of highly complex, unstructured financial documents, enabling us to deliver data with unprecedented accuracy, speed, and trust. You’ll work hands‑on with LLM and other ML Models, helping scale Canoe’s platform while shaping how alternative investment firms interact with their data.

What You’ll Do
  • Design, train, and evaluate ML models for document classification, entity extraction, summarization, and information retrieval.

  • Fine-tune and optimize large language models for domain specific use cases, optimizing their performance for accuracy, efficiency, and scalability.
  • Work closely with data engineering teams to preprocess and engineer features from large datasets to enhance the performance of machine learning models.
  • Build scalable, production‑ready ML services with strong observability, monitoring, and retraining capabilities.
  • Contribute to Canoe’s MLOps stack, including CI/CD for models, feature stores, evaluation frameworks, and data versioning.
  • Collaborate with product managers, software engineers, and other stakeholders to integrate machine learning models into end‑to‑end solutions.
  • Stay current with advancements in LLMs, Agentic AI, and ML, and translate new research into practical improvements to Canoe’s technology stack.
  • Conduct code reviews to ensure code quality and provide mentorship to junior members of the machine learning team.
What We’re Looking For
  • Minimum of 5 years of experience in applied ML engineering, with a focus on NLP, information extraction, or LLMs.
  • Proficiency in Python and relevant machine learning libraries (e.g., TensorFlow, PyTorch).
  • Strong understanding of MLOps (Docker, Kubernetes, CI/CD for ML, experiment tracking).
  • Proficiency with AI‑assisted development tools (e.g., GitHub Copilot, Claude Code agent) to accelerate software development, prototyping, testing, and deployment of ML solutions.
  • Problem‑solver with a product mindset and bias toward outcomes.
  • Excellent communication skills; able to partner across engineering, product, and business teams.
  • Comfortable in fast‑paced, agile startup environments.
  • Bachelor’s degree in computer science or related field.
Preferred
  • Master Degree or PhD in computer science or related field
  • Experience in training and deploying large language models.
  • Familiarity with cloud computing platforms and distributed computing.
  • Familiarity with modern ML Ops tools such as Modal, Weights and Biases, Sagemaker, etc.
  • Experience with LLM fine‑tuning techniques such as LoRA, QLoRA, or parameter‑efficient training frameworks (e.g., Unsloth).
What You’ll Get
  • Medical, dental, vision benefits
  • Flexible PTO
  • 401(k)
  • Flexible work from home policy
  • Home office stipend
  • Employee Assistance Program
  • Gym/Wifi reimbursement
  • Education assistance
  • Parental Leave
Our Values
  • Client First —> Listen, and deliver client‑centric solutions
  • Be An Owner —> Take initiative, improve situations, drive positive outcomes
  • Excellence —> Always set the highest standard for yourself and others
  • Win Together —> 1 + 1 = 3
Who We Are

Canoe is reimagining alternative investment data processes for hundreds of leading institutional investors, capital allocators, asset servicing firms and wealth managers. By combining industry expertise with the most sophisticated data capture technologies, Canoe’s technology automates the highly‑frustrating, time‑consuming, and costly manual workflows related to alternative investment document and data management, extraction and delivery. With Canoe, clients can refocus capital and human resources on business performance and growth, increase efficiency, and gain deeper access to their data. Canoe’s AI‑driven platform was developed in 2013 for Portage Partners LLC, a private investment firm.

Canoe is an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

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