Senior Machine Learning Engineer, Simulation Job at PlusAI (Santa Clara)

Senior Machine Learning Engineer, Reinforcement Learning

About the Role: We are looking for a Senior Machine Learning Engineer with stron...

Location

United States , Beverly Hills, CA

Salary:

150000.00 - 185000.00 USD / Year

Snail Games

Expiration Date

Until further notice

Requirements

Strong foundation in machine learning, with hands-on experience building, training, and iterating on applied ML systems
Professional or substantial project experience with reinforcement learning, agent-based systems, sequential decision-making, or closely related areas
Strong Python skills and experience with modern ML frameworks such as PyTorch
Experience designing experiments, evaluating model behavior, and improving results through systematic iteration
T-shaped capability: deep machine learning expertise plus practical range across one or more adjacent areas such as simulation, evaluation, model integration, systems collaboration, or robotics-adjacent machine learning
Strong problem-solving ability, sound judgment, and comfort working in ambiguous, fast-changing environments
Respectful, low-ego collaborative style and willingness to work beyond a narrow specialty when the work requires it

Job Responsibility

Design, train, and iterate on machine learning models for intelligent agents and decision-making systems, with an emphasis on reinforcement learning and related approaches
Define and refine state representations, action spaces, reward structures, and evaluation criteria to improve agent behavior
Build and improve practical experimentation and training workflows, including data generation, experiment tracking, and reproducibility
Analyze results, debug model behavior, and make pragmatic tradeoffs between model performance, iteration speed, and system complexity
Work closely with engineers and other partners to help integrate successful ML work into usable product systems
Contribute thoughtful technical input on next-step experiments, tooling, and ML direction as Egofold continues to evolve

What we offer

True focus on work/life balance
Paid company holidays, vacation, and separate sick leave
Medical, dental, vision, and Life/LTD
401k with company match

Fulltime

Senior Machine Learning Engineer - Forecasting

We are seeking a Senior Machine Learning Engineer, Forecasting to join the Forec...

Location

United States , Los Angeles

Salary:

156190.05 - 211315.95 USD / Year

Amgen

Expiration Date

Until further notice

Requirements

Doctorate degree OR Master's degree and 2 years of applying data science in enterprise environments experience OR Bachelor's degree and 4 years of applying data science in enterprise environments experience OR Associate's degree and 8 years of applying data science in enterprise environments experience OR High school diploma / GED and 10 years of applying data science in enterprise environments experience

Job Responsibility

Design, build, and maintain scalable machine learning systems and forecasting pipelines to support demand forecasting across near-, medium-, and long-term planning horizons
Productionize advanced statistical, Bayesian, and machine learning forecasting models, including training, validation, deployment, and lifecycle management
Build and optimize data pipelines, feature engineering workflows, and batch and real-time inference systems using large, complex datasets
Own the end-to-end ML engineering lifecycle, including solution design, prototyping, model integration, testing, deployment, monitoring, observability, and continuous improvement
Develop robust MLOps capabilities, including model versioning, CI/CD, automated retraining, performance monitoring, drift detection, and rollback strategies
Partner closely with data scientists and business stakeholders to operationalize forecasting, simulation, and scenario-analysis capabilities that support strategic decision-making
Establish and promote software engineering best practices, including code quality, documentation, reproducibility, and system reliability
Research and evaluate emerging tools, platforms, and methodologies in machine learning engineering, forecasting, and AI for potential application to business problems

What we offer

A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts
A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
Stock-based long-term incentives
Award-winning time-off plans
Flexible work models where possible

Fulltime

Senior Machine Learning Engineer - Model Evaluations

The Public Sector ML team at Scale deploys advanced AI systems—including LLMs, a...

Location

United States , San Francisco; St. Louis; New York; Washington

Salary:

216300.00 - 300300.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

Experience in computer vision, deep learning, reinforcement learning, or NLP in production settings
Strong programming skills in Python
experience with TensorFlow or PyTorch
Background in algorithms, data structures, and object-oriented programming
Experience with LLM pipelines, simulation environments, or automated evaluation systems
Ability to convert research insights into measurable evaluation criteria
This role will require an active security clearance or the ability to obtain a security clearance

Job Responsibility

Develop and maintain automated evaluation pipelines for ML models across functional, performance, robustness, and safety metrics, including LLM-judge–based evaluations
Design test datasets and benchmarks to measure generalization, bias, explainability, and failure modes
Build evaluation frameworks for LLM agents, including infrastructure for scenario-based and environment-based testing
Conduct comparative analyses of model architectures, training procedures, and evaluation outcomes
Implement tools for continuous monitoring, regression testing, and quality assurance for ML systems
Design and execute stress tests and red-teaming workflows to uncover vulnerabilities and edge cases
Collaborate with operations teams and subject matter experts to produce high-quality evaluation datasets

What we offer

Comprehensive health, dental and vision coverage
retirement benefits
a learning and development stipend
generous PTO

Fulltime