Machine Learning Researcher Engineer Job at Helpcare AI (New York)

Research Engineer / Machine Learning Engineer - B2B Applications

OpenAI is at the forefront of artificial intelligence, driving innovation and sh...

Location

United States , San Francisco

Salary:

295000.00 - 445000.00 USD / Year

OpenAI

Expiration Date

Until further notice

Requirements

Master's/ PhD degree in Computer Science, Machine Learning, or a related field
2+ years of professional engineering experience (excluding internships) in relevant roles at tech and product-driven companies
Demonstrated experience in deep learning and transformers models
Proficiency in frameworks like PyTorch or Tensorflow
Strong foundation in data structures, algorithms, and software engineering principles
Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization
Excellent problem-solving and analytical skills, with a proactive approach to challenges
Ability to work collaboratively with cross-functional teams
Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines
Enjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done.

Job Responsibility

Innovate and Build: Design and build advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact
Collaborate with the Best: Work closely with software engineers, product managers and forward deployed engineers to understand complex business challenges, address customer concerns and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives
Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches
Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices
Make a Difference: Monitor and maintain deployed models to ensure they continue delivering value. Your work will directly influence how AI benefits individuals, businesses, and society at large.

What we offer

Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
401(k) retirement plan with employer match
Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
Mental health and wellness support
Employer-paid basic life and disability coverage
Annual learning and development stipend to fuel your professional growth
Daily meals in our offices, and meal delivery credits as eligible

Fulltime

New

Machine Learning Engineer 2

FreeWheel, a Comcast company, provides comprehensive ad platforms for publishers...

Location

United States , New York

Salary:

126147.20 - 189220.80 USD / Year

Comcast Advertising

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field of study
1-2 years of relevant professional experience
Strong understanding of software development principles, data structures, and algorithms
Proficient in Python, with a good grasp of common design patterns and backend system design principles, experience with C++ is a bonus
Solid understanding of testing methodologies, with hands-on experience in backend testing tools such as pytest, etc., to ensure code quality and system reliability
Strong problem-solving and debugging skills in backend systems
Good communication and writing skills, coupled with the ability to thrive in a fast-paced, dynamic environment
Familiarity with the Scrum Agile collaboration framework and experience using Jira are a plus
Familiarity with CI/CD tools, Git, and understanding of DevOps principles, experience with Jenkins is a plus
Experience with Docker, Kubernetes, or cloud computing platforms is a plus

Job Responsibility

Implementing, refining, and validating machine learning algorithms tailored for company products and applications
Training machine learning models, validating their accuracy, and manage the deployment of these models into production environments
Designing and developing data pipelines, ensuring proper data ingestion, validation, cleaning, and monitoring
Researching and authoring documentation and technical requirements, including white papers, test results, and formal recommendations
Innovating by contributing to the creation of patents, Application Programming Interfaces (APIs), and other intellectual property
Testing and evaluating machine learning solutions from internal and external sources, providing detailed assessments
Conducting case studies and compile reports to inform testing strategies and results
Designing proof of concept solutions, contributing to research studies that underpin future product or application development
Consistent exercise of independent judgment and discretion in matters of significance
Regular, consistent and punctual attendance. Must be able to work nights and weekends, variable schedule(s) as necessary

What we offer

Paid Time off
Physical Wellbeing
Financial Wellbeing
Emotional Wellbeing
Life Events + Family Support
Bonus

Fulltime

New

Machine Learning Engineer (MLOps Lead)

Role Highlights: Position: Machine Learning Engineer (MLOps Lead) Location: Lond...

Location

United Kingdom , London

Salary:

Not provided

RED Commerce - The Global SAP Solutions Provider

Expiration Date

Until further notice

Requirements

Strong MLOps / ML Engineering experience (5+ years)
Hands-on experience with GCP (Vertex AI)
Excellent Python development skills
Experience with CI/CD, Docker, Terraform
Ability to take ML models from research to production
Leadership or mentoring experience

Design Verification Engineer - Machine Learning Accelerators

Reality Labs focuses on delivering Meta's vision through Augmented Reality (AR) ...

Location

United States , Sunnyvale

Salary:

178000.00 - 250000.00 USD / Year

Senior Machine Learning Engineer, Simulation Evaluation

Waymo is an autonomous driving technology company with the mission to be the wor...

Location

United States , Mountain View

Salary:

213000.00 - 263000.00 USD / Year

a16z

Expiration Date

Until further notice

Requirements

Bachelor's, Master's, or PhD in computer science, machine learning, robotics, or a related field
Five or more years of experience in machine learning engineering or applied deep learning, supported by a portfolio of shipped products or peer-reviewed publications
Proficient programming skills in Python and hands-on experience with modern machine learning frameworks such as Jax, Flax, or PyTorch
Experience designing and implementing evaluation frameworks for complex systems or machine learning models.

Job Responsibility

Lead the design, development and deployment of cutting-edge evaluation approaches to assess realism of state-of-the-art multimodel world models and generative systems for simulation use cases at Waymo
Architect and implement robust and scalable machine learning pipelines for tuning, evaluating, and deploying large-scale discriminator models for the purposes of simulator realism evaluation
Evaluate open-source and production-ready video generation techniques that measure realism (e.g. temporal stability, multi-modal consistency, geometric discrepancy, condition following, etc.)
Apply vision language models to evaluate semantic understanding and controllability across our world simulation products
Collaborate with research teams across Waymo and Alphabet to integrate advancements in 4D world modeling and generative AI into production systems
Mentor engineers on the team and provide technical guidance on architecture and execution.

What we offer

Waymo’s discretionary annual bonus program
equity incentive plan
generous Company benefits program
Health and wellness
Financial wellness
Flexibility and time off

Fulltime

Machine Learning Engineer

Location

United States , Los Angeles

Salary:

Not provided

Robert Half

Expiration Date

Until further notice

Requirements

Lead the design, implementation, and ongoing maintenance of scalable ML infrastructure on Databricks, including ML flow for experiment tracking, model registry, and model serving endpoints
Oversee the development of the ML Ops platform and automated pipelines for deploying, monitoring, and maintaining models within production environments
Implement robust solutions for model versioning, systematic retraining, and comprehensive artifact management using Databricks Unity Catalog for ML governance
Design and manage Databricks Feature Store for consistent feature engineering across training and inference pipelines
Architect and implement Retrieval-Augmented Generation (RAG) systems for document Q&A, enabling business teams to query fund documents, investor letters, and market research
Design, deploy, and manage vector database solutions (Databricks Vector Search, Pinecone, or similar) for semantic search and retrieval across enterprise documents
Lead LLM fine-tuning and customization initiatives, training models like Claude or open-source alternatives with CIM proprietary data while ensuring data privacy and compliance
Develop and optimize document processing pipelines including PDF parsing, chunking strategies, and embedding generation for RAG applications
Implement prompt engineering best practices and LLM evaluation frameworks to ensure output quality, relevance, and factual accuracy
Build guardrails and safety measures for GenAI applications, including hallucination detection, output validation, and source attribution

Job Responsibility

ML Model Deployment & Platform Management
Generative AI & LLM Operations
Automation & CI/CD Pipelines

What we offer

medical
vision
dental
life and disability insurance
401(k) plan

Machine Learning Engineer

We are looking for a Machine Learning Engineer to build and support production-r...

Location

United States , Los Angeles

Salary:

Not provided

Robert Half

Expiration Date

Until further notice

Requirements

5+ years of experience in machine learning engineering, MLOps, or a closely related technical role
Strong proficiency in Python and practical experience building machine learning solutions in production environments
Hands-on expertise with Databricks and familiarity with capabilities such as experiment tracking, model governance, workflows, and feature management
Experience deploying and maintaining generative AI or large language model applications, including retrieval-based architectures and vector databases
Solid understanding of automation, CI/CD practices, and workflow orchestration for data and model pipelines
Background working with machine learning frameworks such as TensorFlow and applying AI techniques in real-world business settings
Knowledge of model evaluation, monitoring, and governance practices with attention to reliability, compliance, and traceability

Job Responsibility

Build and maintain scalable machine learning infrastructure in Databricks, including experiment tracking, model management, and serving capabilities for production use
Create and improve MLOps frameworks and automated deployment pipelines that support model release, monitoring, and lifecycle management
Establish disciplined processes for model version control, retraining, and artifact governance using tools such as Unity Catalog
Develop and administer a feature store strategy that keeps training and inference data consistent across machine learning workflows
Design retrieval-augmented generation solutions that allow internal teams to search and interact with documents such as fund materials, investor communications, and research content
Implement and manage vector search platforms to support semantic retrieval across large collections of enterprise documents
Customize and fine-tune large language models using proprietary datasets while protecting data privacy and meeting compliance expectations
Build document ingestion and transformation pipelines that handle parsing, segmentation, and embedding creation for generative AI applications
Introduce prompt design standards, evaluation methods, and application safeguards to improve response quality, reduce hallucinations, and provide source-backed outputs
Automate training, testing, orchestration, and deployment workflows through CI/CD pipelines and tools such as Databricks Workflows, GitHub Actions, Azure DevOps, Airflow, or Prefect

What we offer

Medical, vision, dental, and life and disability insurance
Company 401(k) plan

Senior Machine Learning Engineer

Join Amgen’s Mission of Serving Patients. At Amgen, if you feel like you’re part...

Location

United States , Thousand Oaks

Salary:

158606.00 - 200052.00 USD / Year

Amgen

Expiration Date

Until further notice

Requirements

Bachelor’s degree (or foreign equivalent) in Computer Science, Statistics, Electrical Engineering, Mathematics, Bioengineering or a related field and 4 years of experience in the job offered or in a Data Scientist related – Occupation
4 years of experience in the following: 1) Programming skills in Python including experience with scientific computing and machine learning libraries including pandas, NumPy, scikit-learn, XGBoost, LightGBM, TensorFlow and PyTorch
2) Applying supervised and unsupervised learning techniques to real-world problems, including experience with Random Forest, XGBoost, ensemble models, and deep learning architectures
3) Version control (Git), containerization and orchestration tools including Docker and Kubernetes, and cloud environments including AWS or GCP
4) Involved with data science platforms including Databricks and SageMaker
5) Using statistical methods industry including regression modeling, hypothesis testing, Bayesian methods, Forecasting techniques and time-series analysis
6) Building ETL (Extract, Transform, Load) pipelines for handling large-scale, high-dimensional datasets, familiarity with healthcare data structures and data types
7) Experience with software DevOps CI/CD tools and GitLab
8) Experience developing and fine-tuning Natural Language Processing (NLP) models, including work with architectures such as BERT, ALBERT, GPT, and other transformer-based models.

Job Responsibility

Lead efforts with Amgen business leaders to identify, explore and develop transformative AI and ML solutions to enable access to computational tools and data within Amgen, and ultimately improve patient outcomes across multiple therapeutic areas
Utilize Cloud Services to collect, store, preprocess, and analyze large datasets from various sources across Amgen
Collaborate with other ML engineers, data scientists and research scientists to identify appropriate ML models and algorithms
Facilitate ML & Data engineering efforts by architecting and guiding the implementation of data and ML pipelines for development and deployment
Facilitate model deployment to production, including monitoring and maintenance of ML models, put in place metrics to assess accuracy and drift
Define model evaluation and validation strategies, train and test models, and analyze and resolve errors and biases in models
Lead and develop standards, processes, and best practices for the team across the machine learning-based solution implementation lifecycle
Involved in technical guide and career development mentor to junior machine learning engineers and data scientists in a formal or matrixed fashion.

What we offer

stock
retirement
medical
life and disability insurance
eligibility for an annual bonus or for sales roles, other incentive compensation
Retirement and Savings Plan with generous company contributions
group medical, dental and vision coverage
life and disability insurance
flexible spending accounts
discretionary annual bonus program

Fulltime

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Machine Learning Researcher Engineer

Job Description

Job Responsibility

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