ZipRecruiter

Log In

1

Director Machine Learning Jobs in Massachusetts (NOW HIRING)

Iambic Therapeutics, Inc

$148K - $186K/yr

JOB SUMMARY We are seeking a Machine Learning Scientist to join the Enchant team at Iambic ... Direct exposure to multi-task learning * Hands-on experience with agentic data extraction * HPC or ...

next page

Showing results 1-20

All JobsMachine Learning JobsDirector Machine Learning JobsDirector Machine Learning Jobs in Massachusetts

Director Machine Learning information

See Massachusetts salary details

$39.3K

$100.4K

$154K

How much do director machine learning jobs pay per year?

As of Jul 14, 2026, the average yearly pay for director machine learning in Massachusetts is $100,402.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,100.00 and $115,800.00 per year, depending on experience, location, and employer.

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.

What is a Director Machine Learning job?

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 of 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 most commonly searched types of Machine Learning jobs in Massachusetts? The most popular types of Machine Learning jobs in Massachusetts are:
What are popular job titles related to Director Machine Learning jobs in Massachusetts? For Director Machine Learning jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Director Machine Learning jobs in Massachusetts look for? The top searched job categories for Director Machine Learning jobs in Massachusetts are:
What cities in Massachusetts are hiring for Director Machine Learning jobs? Cities in Massachusetts with the most Director Machine Learning job openings:
Director Machine Learning jobs near you
Infographic showing various Director Machine Learning job openings in Massachusetts as of July 2026, with employment types broken down into 1% As Needed, 78% Full Time, 18% Part Time, 2% Temporary, and 1% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution, with an average salary of $100,402 per year, or $48.3 per hour.
Founding Machine Learning Engineer

Founding Machine Learning Engineer

OneScreen

Boston, MA • On-site

Full-time

Posted 29 days ago

Job description

About Onescreen
Onescreen is the modern platform for out-of-home advertising - making it easier for brands and agencies to plan, buy, and measure OOH campaigns across thousands of vendors and formats. We move fast, operate lean, and hold ourselves to a high standard on every campaign we run.
About the role
You'll be the founding ML engineer who owns our matching algorithms from exploration through production and the data platform that feeds them. You'll design and ship the models that rank OOH inventory against advertiser personas, markets, and dayparts. You'll own our data warehouse shape and the pipelines that fill it. You'll publish the ranking and matching APIs that downstream products, agents, and automation surfaces consume.
What you'll do
  • Design and ship matching and ranking models for OOH inventory: candidate generation, re-ranking, geospatial-aware scoring.
  • Own the data warehouse layer end to end: staging, marts, feature pipelines, freshness, lineage.
  • Stand up offline and online evaluation infrastructure - measure the gap between them, don't assume it.
  • Publish ranking and matching APIs for product surfaces, with latency and quality SLOs.
  • Instrument model monitoring: drift detection, prediction distribution, feature freshness, retraining triggers.

Qualifications
The hard requirement: you have owned a production ranking, matching, or recommendation system end-to-end. You chose the model, designed the features, made the evaluation methodology calls, and were on the hook when it drifted. We care about that ownership scope more than years on a résumé - title and compensation are scaled to your demonstrated expertise.
Beyond that:
  • Strong production Python (NumPy, Pandas, FastAPI, SQLAlchemy).
  • Strong SQL and modern data warehouse experience (BigQuery preferred).
  • Real ranking and matching modeling fluency - learning-to-rank, retrieval and re-rank patterns, not just classification.
  • Evaluation methodology rigor: holdouts, leakage prevention, online vs. offline gap measurement.
  • Comfort owning the data pipeline as well as the model.
  • Bias toward shipping. Clear writer. Self-directed.
Nice to have
  • Geospatial data experience (H3, PostGIS, GeoPandas)
  • Mobility or location data experience
  • Embedding-based retrieval (pgvector, FAISS, vector databases)
  • Bandits, contextual bandits, or online learning
  • A/B testing infrastructure design
  • Causal inference
  • dbt
  • Ad-tech or OOH domain familiarity

Apply