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Afternoon Full Stack Machine Learning Engineer Jobs

Machine Learning Engineer Location: Long Island City, NY 11101 (Onsite 4 Days/week) Type: Permanent ... Collaborate closely with product managers, full-stack engineers, and TPMs to ensure seamless ...

Machine Learning Engineer New York, NY | Full Time COMPENSATION RANGE: 140,000.00 - 170,000.00 (On ... and deploying full-stack scalable data analytics and machine learning solutions to challenge ...

Machine Learning Engineer - Senior Level Bellevue, WA - HQ Your Skills: * Experience with cloud ... Create a boutique "GPU-first" cloud stack optimized and focused on AI/Client workloads * Create ...

Machine Learning Engineer We're looking for a talented and motivated Machine Learning Engineer to ... Tackle a wide variety of technical problems throughout the stack and contribute daily to all parts ...

Senior/Principal Machine Learning Engineer

Seattle, WA · On-site

$142K - $196K/yr

We're forming small, senior, cross-functional AI teams that bring together product leaders, machine learning engineers, and full-stack builders to create intelligent agents used by millions of people ...

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How much do afternoon full stack machine learning engineer jobs pay per year?

As of Jun 20, 2026, the average yearly pay for afternoon full stack machine learning engineer in the United States is $134,771.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $158,000.00 per year, depending on experience, location, and employer.
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Machine Learning Engineer

Full-time

Posted 27 days ago


Job description

Job Title: Machine Learning Engineer
Location: Long Island City, NY 11101
(Onsite 4 Days/week)
Type: Permanent Full Time
About the Role:
In this role, you will take the lead in developing and fine-tuning predictive ML models, with a primary focus on Ad Score and Ad Account Health.
Responsibilities include but are not limited to;
ML Model Development: Lead the development and refinement of predictive ML models, particularly Ad Score and Ad Account Health.
Data Analysis: Conduct in-depth data analysis to identify trends, patterns, and insights that inform model development and optimization.
Feature Engineering: Collaborate with data engineers to create and maintain feature engineering pipelines to support model training.
Model Evaluation: Implement rigorous evaluation methodologies to assess model performance, making necessary adjustments for continuous improvement.
Deployment and Integration: Work closely with engineering teams to deploy models and integrate them into our products through APIs.
Collaboration: Collaborate closely with product managers, full-stack engineers, and TPMs to ensure seamless integration of data science solutions into our products.
Research and Innovation: Stay up-to-date with the latest developments in the field of data science and machine learning, and explore innovative approaches to problem-solving.
Requirements
  1. Master's or Ph.D. in a related field with a strong academic background.
  2. Proven experience as a Data Scientist with a track record of developing and deploying predictive ML models.
  3. Expertise in machine learning techniques, including but not limited to regression, classification, clustering, and deep learning.
  4. Proficiency in data manipulation, feature engineering, and model evaluation.
  5. Strong programming skills in languages such as Python and experience with libraries like TensorFlow, PyTorch, or scikit-learn.
  6. Excellent communication skills and the ability to collaborate effectively within cross-functional teams.
  7. A passion for continuous learning and staying updated with the latest trends and technologies in data science.
  8. Strong problem-solving abilities and the capacity to translate complex data into actionable insights.

Required knowledge of:
  1. Python
  2. SQL
  3. Cloud Platforms (GCP, AWS, Azure)
  4. Data Warehouses (BigQuery, Snowflake, Redshift)
  5. LLMs / AI APIs
  6. Git / GitHub

Nice to have:
Data Transformation (dbt)
Semantic Layers (Cube, Looker, dbt Metrics)
TypeScript
Bayesian modeling experience - ideally Marketing Mix Models (PyMC, Stan, or similar..). Understands priors, MCMC sampling, posterior diagnostics.
Causal inference / experimentation- geo experiments (matched markets), A/B testing at scale. Familiar with incrementality measurement.
Marketing/advertising domain- understanding of attribution, media channels (paid social, search, display, video), campaign structures.
Nice to have - familiarity with adstock/saturation curves and budget optimization
Our interview process includes, but is not limited to the following:

InstantServe logo

About InstantServe

Sourced by ZipRecruiter

InstantServe provides a one-stop solution to all Healthcare, IT/Non-IT Staffing needs. Established in 2016, InstantServe is a strong workforce of over 100+ go-getters with a demonstrated background in IT/Non-IT service. We are a nationally certified SBE from the Department of Administration (State of PA). As a proud Minority Woman Owned Small Business Enterprise (M/WBE), InstantServe boasts of a strong team of professionals who have extensive experience catering to several Federal, Public, Commercial, and Healthcare Clients which includes 26 States and 46 government agencies. InstantServe is a client-centric organization that offers cost-effective and reliable solutions. Client satisfaction is sacrosanct! Our team strives to provide the best staffing and IT solutions to take your business to the next level.

Industry

Recruiting and staffing services

Company size

11 - 50 Employees

Headquarters location

Wayne, PA, US

Year founded

2016

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