Kubeflow

Kubeflow Data Jobs

5 jobs found

3d ago

Machine Learning Engineer

Amgen Remote 🇺🇸 Remote

Remote

3d ago

$130k - $175k/yr Full time Ai Ml Artificial Intelligence AWS

Apply Now

Job Description

Benefits

Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts
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

About Amgen and our culture

Amgen is dedicated to advancing treatments that improve patient lives. Since 1980, we have been at the forefront of biotech, focusing on Oncology, Inflammation, General Medicine, and Rare Disease. This role supports scientists across Amgen in building, deploying, and managing AI and ML solutions for drug discovery and development, all within a collaborative, growth-minded environment.

What you will do

Deliver AI and ML enabled applications with models spanning classical algorithms to natural language processing, protein language models, and large language models
Contribute to ML platform capabilities such as data pipelines and feature engineering workflows
Contribute to model training, evaluation, and deployment pipelines
Contribute to experiment tracking and model registry systems
Contribute to model performance evaluations and monitoring
Partner in implementing AI and ML Ops best practices, including CI/CD, infrastructure as code, monitoring, traceability and reproducibility
Collaborate with cross-functional teams to transition experimentation outcomes into production-grade enterprise solutions
Build and maintain scalable, productionized MLOps solutions on cloud platforms
Develop and deliver training content and knowledge articles to educate resident scientists on model lifecycle management best practices

Requirements

Master’s degree
Bachelor’s degree and 2 years of experience in Computer Science, IT, or engineering
Associate’s degree and 6 years in Computer Science, IT, or engineering
High school diploma / GED and 8 years in Computer Science, IT, or engineering
Software programming (Python, version control, test-driven development)
Familiarity with cloud technologies (AWS preferred, Databricks)
Hands-on experience with AI/ML model training and serving

Technologies

Python, Databricks, AWS, Azure
MLflow, Kubeflow, Weights & Biases
Terraform, Docker, Kubernetes
Spark, scikit-learn, TensorFlow, PyTorch
LangChain

Compensation and Location

Salary: USD 129,654 - 175,415 per year

Location: Remote (remote); remote work in the US is eligible

Education requirements note: Master’s degree is required; alternative combinations are listed in the requirements above.

Additional details

Application details and sponsorship: Amgen does not set a formal application deadline and continues accepting applications until a suitable candidate is found. Sponsorship for this role is not guaranteed.

View full job page →

3d ago

Machine Learning Engineer

Intone Networks Remote 🌍 Remote

Remote

3d ago

Full time Ai Ml Artificial Intelligence Automation

Apply Now

Job Description

Intone Networks is seeking a Machine Learning Engineer to design, optimize, and maintain scalable ML pipelines and systems. The role involves close collaboration with data scientists, software engineers, and cross-functional teams to deploy production‑ready models with robust CI/CD processes in a remote setting.

Responsibilities

Design, develop, and productionize reliable ML pipelines within a fast-paced environment.
Collaborate with data scientists, engineers, and cross-functional partners to translate models into dependable, scalable production systems.
Own end-to-end ML lifecycle activities, including data ingestion, feature engineering, model training, deployment, monitoring, and iteration.
Implement and maintain CI/CD workflows for ML applications to enable rapid, dependable releases.
Troubleshoot and optimize complex pipeline issues to meet tight timelines.
Foster a positive, high-performing team culture through clear communication, knowledge sharing, and proactive problem-solving.

Requirements

Strong Python expertise with practical experience building production-grade ML applications.
Demonstrated ability to collaborate effectively in a team environment under tight deadlines and complex technical challenges.
Solid understanding of machine learning operations (MLOps) best practices.
Experience with containerization using Docker.
Proficiency with Git and version control workflows, including GitHub Actions.
Strong problem-solving abilities and a collaborative, team-first mindset.

Technologies

Key tools and platforms involved in this role include:

Python
Docker
Git
GitHub Actions
Kubeflow
Snowflake
Datadog
Windsurf
Devin
Cursor
Claude Code

Preferred Qualifications

(Major plus)

Hands-on experience with Kubeflow for orchestrating ML workflows.
Familiarity with Snowflake for data warehousing and analytics.
Experience with observability and monitoring tools, particularly Datadog.
Background in building and managing CI/CD pipelines for ML or data systems.
Experience using AI-assisted development tools such as Windsurf, Devin, Cursor, or Claude Code to accelerate development.

View full job page →

13d ago

Senior Data Scientist, Cloud Gaming - Prescriptive Analytics and Optimization

NVIDIA Santa Clara, CA

Santa Clara, CA

13d ago

$184k - $288k/yr Full time Senior Analytics Big Data

Apply Now

Job Description

This senior data scientist role focuses on prescriptive analytics and optimization for real-time cloud gaming, delivering scalable ML/AI and optimization solutions for routing, scheduling, and capacity management at NVIDIA.

Location

Santa Clara, CA (onsite)

Compensation

USD 184,000 - 287,500 per year

Experience and Education

Minimum 6 years of experience with a BS/MS or equivalent experience, or a PhD in Data Science, Computer Science, Operations Research, Statistics, Applied Mathematics, or a related quantitative field.

Responsibilities

Develop and deploy scalable ML, AI, and optimization models to improve demand forecasting, optimize capacity allocation, and implement user-specific feature engineering for real-time cloud gaming services.
Create reusable framework deployments for data ingestion, processing, and analysis to support dynamic user interventions toward targeted business outcomes.
Apply domain knowledge of the product and software stack to identify data inconsistencies and enhance model performance, especially in the context of optimization results.
Analyze complex datasets to identify trends and patterns using supervised and unsupervised learning to inform prescriptive solutions.
Design and enhance real-time prescriptive scheduling pipelines using linear programming and constraint optimization to improve capacity utilization and user retention.
Increase organizational productivity by mining petabytes of data for actionable insights, often delivered as prescriptive recommendations.
Collaborate with a diverse set of partners to gather requirements, design robust solutions, and guide the team toward impactful results.
Leverage agentic AI to deliver advanced automation and programming solutions for complex analytical problems.

Requirements

BS/MS (or equivalent experience) with 6+ years of experience or PhD in Data Science, Computer Science, Operations Research, Statistics, Applied Mathematics, or related quantitative fields, with a focus on prescriptive analytics and optimization.
Strong foundation in probability, statistics, AI/ML, prescriptive modeling, and optimization methodologies such as linear programming, network flow, decision theory, and multi-armed bandit.
Proficient coding skills, primarily Python, with the ability to write readable, testable, maintainable, and extensible code; experience with optimization libraries such as Google OR-Tools.
Experience with data storage and processing tools and the ability to address issues in running large-scale software across substantial clusters.
Solid experience in data cleaning, aggregation, transformation, and extraction, with an understanding of how data quality affects performance.

Technologies

Python
SQL
Delta Lake
Apache Spark
Databricks
MLflow
Grafana
Elasticsearch
Google OR-Tools
Kubeflow

Benefits

Equity
Benefits

What you will be doing

Develop and deploy scalable ML, AI, and optimization models to improve demand forecasting, optimize capacity allocation, and craft user-specific features for real-time cloud gaming services.
Build reusable data ingestion, processing, and analysis frameworks to support dynamic user interventions for targeted business outcomes.
Apply product and software stack knowledge to resolve data inconsistencies and boost model performance within optimization contexts.
Identify and interpret patterns in complex data using supervised and unsupervised methods to inform prescriptive solutions.
Enhance real-time prescriptive scheduling pipelines through linear programming and constraint optimization to maximize capacity utilization and retention.
Drive organizational productivity by mining vast data stores for actionable insights and prescriptive guidance.
Collaborate with partners to define requirements, craft robust solutions, and lead the team toward meaningful results.
Utilize agentic AI to deliver automation and programming solutions for challenging analytical problems.

What we need to see

BS/MS (or equivalent experience) with 6+ years of experience or PhD in Data Science, Computer Science, Operations Research, Statistics, Applied Mathematics, or related quantitative fields, with a strong emphasis on prescriptive analytics and optimization.
Solid background in probability, statistics, AI/ML, prescriptive modeling, and optimization methods (eg, linear programming, network flow, decision theory, multi-armed bandit).
Strong coding ability in Python with experience in optimization libraries such as Google OR-Tools; ability to write clean, maintainable code.
Experience with data storage and processing tools and handling large-scale distributed software across clusters.
Proficiency in data cleaning, aggregation, transformation, and extraction, with awareness of data quality impacts on performance.

Ways to stand out from the crowd

Strong collaboration and presentation skills for working with multiple partners, with the ability to explain complex analytical solutions and their business implications.
Experience in time series analysis and forecasting for demand prediction in optimization contexts is advantageous.
Experience operating active ML production pipelines (MLflow, Kubeflow) with a focus on deploying and monitoring optimization models is advantageous.

View full job page →

1mo ago

Machine Learning Engineer, Motion Planning & Prediction

Avride Austin, TX

Austin, TX

1mo ago Closed

Full time Ai Ml Artificial Intelligence Big Data

This position is no longer accepting applications (closed Jul 16, 2026).

Job Description

Avride is seeking a Machine Learning Engineer to join its autonomous vehicle team focused on motion planning and prediction in Austin, TX (onsite).

Responsibilities

Design, train, and deploy advanced ML models for behavioral prediction and motion planning.
Build robust data pipelines to process, clean, and label large-scale vehicle sensor and simulation datasets.
Leverage transformers and other deep learning architectures to capture temporal interactions among traffic agents.
Define and own model performance metrics; develop evaluation frameworks aligned with on-road safety and performance.
Collaborate with software engineers to integrate and optimize models for real-time on-vehicle embedded hardware inference.
Stay current with ML research, including imitation learning and reinforcement learning, and apply novel techniques to the systems.

Requirements

Strong Python skills and hands-on experience with modern deep learning frameworks such as PyTorch, TensorFlow, or JAX.
Solid grounding in ML fundamentals, including neural network architectures, training methodologies, and evaluation techniques.
Experience across the ML lifecycle, from data exploration and prototyping to deployment and monitoring.
Proficiency in C++ for high-performance model inference code.

Technologies

Python
PyTorch
TensorFlow
JAX
C++
MLflow
Kubeflow
Weights & Biases
Spark
Ray

Nice to Have

Strong track record in ML competitions such as Kaggle or notable contributions to major open-source ML projects.
Experience applying ML to robotics problems like behavioral prediction, motion planning, or computer vision.
Experience with MLOps tools and platforms such as MLflow, Kubeflow, Weights & Biases.
Experience with large-scale distributed data processing and training frameworks such as Spark or Ray.
Publications in top ML or robotics conferences (e.g., NeurIPS, ICML, CVPR, ICLR, CoRL, RSS).

View full job page →

2mo ago

Machine learning Engineer

Tata Consultancy Services Pennington, NJ

Pennington, NJ

2mo ago Closed

$105k - $125k/yr Full time Analytics Artificial Intelligence Automation

This position is no longer accepting applications (closed Jun 8, 2026).

Job Description

Benefits

Join Tata Consultancy Services in Pennington, NJ and access a comprehensive benefits package that supports your health, finances, and ongoing professional growth.

Discretionary Annual Incentive
Medical Coverage (Medical & Health, Dental & Vision)
Disability Insurance
Pet Insurance
Maternal & Parental Leaves
Auto & Home Insurance
Identity Theft Protection
Commuter Benefits
Certification & Training Reimbursement
Vacation, Time Off, Sick Leave & Holidays
401K Plan
Performance Bonus
College Fund
Student Loan Refinancing

Overview

This onsite Machine Learning Engineer role at Tata Consultancy Services is based in Pennington, NJ. It emphasizes hands-on data science, model development, and building scalable ML data pipelines to deliver production-ready solutions. The position requires a Bachelor of Computer Science and offers a salary range of USD 105,000 - 125,000 per year.

Responsibilities

Hands-on ML engineering with deep experience in data science, model development, and scalable data/ML pipelines.
Delivery of production-ready ML solutions with strong execution and technical craftsmanship.

Requirements

CI/CD for ML using MLflow, Kubeflow, SageMaker, or Azure ML
Model versioning, monitoring, and retraining workflows
Docker and Kubernetes for deployment
Strong Python proficiency (NumPy, pandas, scikit-learn, PyTorch/TensorFlow)
Experience with AWS, Azure, or GCP ML services
Supervised models such as Logistic Regression, Random Forest, XGBoost/LightGBM, SVMs
Deep learning: Neural Networks, CNN, RNN, Transformers (PyTorch or TensorFlow); classification models and evaluation methods (AUC, ROC, precision/recall, cross-validation)
Data cleaning, handling missing values and outliers; feature scaling, encoding, time-series feature generation; strong exploratory data analysis and statistical analysis skills
Building and maintaining ML/data pipelines with Spark, Databricks, Airflow; data ingestion, transformation, validation (Great Expectations preferred)

Technologies

MLflow
Kubeflow
SageMaker
Azure ML
Docker
Kubernetes
Python ecosystem: NumPy, pandas, scikit-learn, PyTorch, TensorFlow
AWS, Azure, GCP ML services
Spark, Databricks, Airflow
Great Expectations
XGBoost, LightGBM
Logistic Regression, Random Forest, SVMs
Neural Networks, CNN, RNN, Transformers

Job Details

Location: Pennington, NJ
Salary: USD 105,000 - 125,000 per year
Education: Bachelor of Computer Science
Job ID: 409540
Job Function: Technology
Role: Engineer

View full job page →

Kubeflow Data Jobs

Machine Learning Engineer

Machine Learning Engineer

Senior Data Scientist, Cloud Gaming - Prescriptive Analytics and Optimization

Machine Learning Engineer, Motion Planning & Prediction

Machine learning Engineer

Get Kubeflow Data Jobs alerts