1

Director Machine Learning Jobs in New Jersey (NOW HIRING)

Director, AI Governance Lead

Jersey City, NJ ยท On-site

$150 - $190/hr

Strong understanding of AI, machine learning, generative AI, automated decisioning, data science workflows, AI system lifecycle risks, and responsible AI principles. * Demonstrated experience ...

Director of Accounts

Teaneck, NJ ยท On-site

$120 - $170/hr

Since 2016, we have developed automated solutions combining computer vision, machine learning, and ... Role Director of Accounts, Car Rental will serve as the primary liaison between UVeye and one or ...

Showing results 21-40

Director Machine Learning information

See New Jersey salary details

$36.5K

$93.3K

$143.1K

How much do director machine learning jobs pay per year?

As of Aug 24, 2026, the average yearly pay for director machine learning in New Jersey is $93,333.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,600.00 and $107,600.00 per year, depending on experience, location, and employer.

What is a director machine learning?

A Director of Machine Learning leads teams in developing and deploying machine learning models to solve business challenges. They define the AI strategy, oversee research, and ensure models are scalable and ethical. This role requires expertise in machine learning, data science, and leadership, as well as collaboration with cross-functional teams. Directors also stay updated on industry advancements and drive innovation within their organizations.

What are the primary responsibilities and challenges faced by a director machine learning on a daily basis?

A Director of Machine Learning is typically responsible for overseeing the development and deployment of machine learning solutions, mentoring technical teams, setting strategic direction for AI initiatives, and ensuring the alignment of projects with organizational goals. Challenges often include balancing innovative research with business priorities, navigating evolving technology landscapes, and coordinating efforts across data science, engineering, and stakeholder teams. This role requires regular collaboration with product managers, executives, and cross-functional departments to prioritize initiatives and communicate complex technical concepts. Successful directors excel at fostering a culture of continuous learning, optimizing team productivity, and staying ahead in a fast-paced, rapidly changing field.

What are the key skills and qualifications needed to thrive in the director machine learning position, and why are they important?

To thrive as a Director Machine Learning, you need advanced expertise in machine learning, statistics, data science, and leadership, typically supported by a master's or Ph.D. in a related field and several years of relevant industry experience. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and data management systems, as well as certifications like AWS Certified Machine Learning or Google Professional Machine Learning Engineer, are commonly required. Exceptional communication, strategic thinking, and team management skills distinguish top candidates in this role. These capabilities are essential for driving organizational AI initiatives, fostering high-performing teams, and delivering impactful business solutions.

Is a machine learning director a high paying job?

A machine learning director typically earns a high salary due to the specialized skills, leadership responsibilities, and experience required for the role. Compensation often includes base salary, bonuses, and stock options, reflecting the demand for expertise in AI and data science. Salaries can vary based on industry, company size, and location, but generally rank among the higher-paying technology leadership positions.

What does a director of machine learning do?

A director of machine learning oversees the development and implementation of machine learning strategies and projects within an organization. They lead teams of data scientists and engineers, set technical goals, ensure project alignment with business objectives, and often collaborate with other departments to integrate AI solutions using tools like Python, TensorFlow, or PyTorch.

What are the most commonly searched types of Machine Learning jobs in New Jersey?

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

What cities in New Jersey are hiring for Director Machine Learning jobs?

Cities in New Jersey with the most Director Machine Learning job openings:

Infographic showing various Director Machine Learning job openings in New Jersey as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 20% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $93,333 per year, or $44.9 per hour.

Associate Director, AI/ML Engineering

Princeton, NJ โ€ข On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 22 days ago


Job description

About Acadia Pharmaceuticals
Acadia is committed to turning scientific promise into meaningful innovation that makes the difference for underserved neurological and rare disease communities around the world. Our commercial portfolio includes the first and only FDA-approved treatments for Parkinson's disease psychosis and Rett syndrome. We are developing the next wave of therapeutic advancements with a robust and diverse pipeline that includes mid- to late-stage programs in Alzheimer's disease psychosis and Lewy body dementia psychosis, along with earlier-stage programs that address other underserved patient needs. At Acadia, we're here to be their difference.
Please note that this position is based in San Diego, CA, South San Francisco, CA, or Princeton, NJ. Acadia's hybrid model requires this role to work in our office three days per week on average.
Position Summary
The Associate Director, AI/ML Engineering serves as a hands-on technical leader driving the design, architecture, and delivery of Generative AI and agentic AI solutions across the enterprise. This role builds scalable multi-agent systems, connects AI solutions to enterprise data and tools, and ensures safe, reliable deployment through robust evaluation and guardrail frameworks. The position also applies strong machine learning and foundation model expertise to deliver high-impact use cases within a regulated biopharmaceutical environment.
Primary Responsibilities
  • Design, build, and deploy agentic AI workflows that automate and transform complex business processes, leveraging multi-agent orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI, or equivalent).
  • Architect and implement MCP servers to expose enterprise tools, APIs, and data sources as standardized capabilities consumable by AI agents.
  • Connect multi-agent systems to enterprise databases, internal APIs, and MCP servers to enable grounded, context-aware, and action-oriented AI solutions.
  • Partner cross-functionally with internal teams to define data contracts, lineage standards, and quality thresholds required for AI/ML use cases.
  • Design and implement agentic memory systems (short-term, long-term, episodic) and planning/reasoning loops to support reliable autonomous task execution.
  • Evaluate agentic system performance across accuracy, reliability, latency, cost, and safety dimensions using structured benchmarks and red-teaming methodologies.
  • Build and maintain guardrail frameworks (input/output filtering, content moderation, policy enforcement, hallucination detection) to ensure the safety, compliance, and trustworthiness of GenAI and agentic solutions.
  • Develop retrieval-augmented generation (RAG) pipelines, including chunking strategies, embedding models, vector store selection, and retrieval optimization for enterprise knowledge bases.
  • Apply prompt engineering, few-shot learning, and fine-tuning techniques to adapt foundation models for domain-specific pharma use cases.
  • Design, develop, validate, and deploy traditional machine learning models (classification, regression, clustering, time-series, survival analysis) to address structured business problems.
  • Build and maintain end-to-end ML pipelines adhering to LLM Ops / ML Ops standards including model registry, evaluation benchmarks, prompt/version control, observability, and rollback procedures.
  • Experience in working with real-world data (RWD), claims data, EHR data, Clinical Study data, translational and biological data and the corresponding databases is a plus.
  • Other responsibilities as assigned.

Education/Experience/Skills
  • Master's or PhD in Machine Learning, Computer Science, Data Science, Information Systems, or a related quantitative discipline
  • Minimum of 7 years of experience in AI/ML engineering, including at least 3 years of hands-on experience with Generative AI and agentic AI systems
  • Expertise in multi-agent frameworks such as LangGraph, AutoGen, CrewAI, Semantic Kernel, or similar technologies
  • Experience building MCP servers and integrating AI systems with enterprise data sources, APIs, and tools
  • Strong experience in RAG pipeline development, embedding models, and vector database technologies
  • Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, scikit-learn, and Hugging Face
  • Experience implementing ML Ops or LLM Ops practices, including model lifecycle management, evaluation, and deployment
  • Ability to travel domestically and internationally as required

Physical Requirements
This role involves regular standing, walking, sitting, and the use of hands for handling or operating equipment. The employee may also need to reach, climb, balance, stoop, kneel, crouch, and maintain visual, verbal, and auditory communication in a standard office environment and while working independently from remote locations. The employee must occasionally lift and/or move up to 20 pounds. This position requires the ability to travel independently overnight and/or work after hours as required by travel schedules or business needs.
#LI-HYBRID
#LI-CS1
In addition to a competitive base salary, this position is also eligible for discretionary bonus and equity awards based on factors such as individual and organizational performance. Actual amounts will vary depending on experience, performance, and location.
Salary Range
$172,000-$215,000 USD
What we offer US-based Employees:
  • Competitive base, bonus, new hire and ongoing equity packages
  • Medical, dental, and vision insurance
  • Employer-paid life, disability, business travel and EAP coverage
  • 401(k) Plan with a fully vested company match 1:1 up to 5%
  • Employee Stock Purchase Plan with a 2-year purchase price lock-in
  • 15+ vacation days
  • 13 -15 paid holidays, including office closure between December 24th and January 1st
  • 10 days of paid sick time
  • Paid parental leave benefit
  • Tuition assistance

EEO Statement (US-based Employees): Studies have shown that women and people of color are less likely to apply for jobs unless they believe they meet every one of the qualifications in the exact way they are described in job postings. We are committed to building a diverse, equitable, inclusive, and innovative company, and we are looking for the BEST candidate for the job. That candidate may be one who comes from a less traditional background or may meet the qualifications in a different way. We strongly encourage you to apply, especially if the reason you are the best candidate isn't exactly what we describe here.
It is the policy of Acadia to provide equal employment opportunities to all employees and employment applicants without regard to considerations of race, including related to hairstyle, color, religion or religious creed, sexual orientation, gender, gender identity, gender expression, gender transition, country of origin, ancestry, citizenship, age, physical or mental disability, genetic information, legally-protected medical condition or information, marital status, domestic partner status, family care status, military caregiver status, veteran or military status (including reserve status, National Guard status, and military service or obligation), status as a victim of domestic violence, sexual assault or stalking, enrollment in a public assistance program, or any basis protected under federal, state or local law.
As an equal opportunity employer, Acadia is committed to a diverse workforce. If you are a qualified individual with a disability or a disabled veteran, you have the right to request a reasonable accommodation. Furthermore, you may request additional support if you are unable or limited in your ability to use or access Acadia's career website due to your disability, along with any accommodations throughout the interview process. To request or inquire about your reasonable accommodation, please complete our Reasonable Accommodation Request Form or contact us at talentacquisition@acadia-pharm.com or 858-261-2923.
Please note that reasonable accommodations granted throughout the recruiting process are not guaranteed to be the same accommodations given if hired. A new request will need to be submitted for any ADA accommodations after starting employment.
California Applicants: Please see Additional Information for California Residents within our Privacy Policy.
Canadian Applicants: Please see Additional Information for Canadian Residents within our Privacy Policy.
Applicants in the European Economic Area, Switzerland, the United Kingdom, and Serbia: Please see Additional Information for Individuals in the European Economic Area, Switzerland, the United Kingdom, and Serbia within our Privacy Policy.
Notice to Search Firms/Third-Party Recruitment Agencies (Recruiters): The Talent Acquisition team manages the recruitment and employment process for Acadia Pharmaceuticals Inc. ("Acadia"). Acadia does not accept resumes from recruiters or search firms without an executed search agreement in place. Resumes sent to Acadia employees in the absence of an executed search agreement will not obligate Acadia in any way with respect to the future employment of those individuals or potential remuneration to any recruiter or search firm. Candidates should never be submitted directly to our hiring managers or employees.