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Kubeflow Engineer Jobs

3 jobs found

2d ago

Machine Learning Engineer

Amgen Remote 🇺🇸 Remote

Remote

2d ago

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

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Job Description

Amgen is seeking a Machine Learning Engineer to build scalable ML platforms for drug discovery and development, with remote work eligibility in the United States.

Responsibilities

Develop and deploy AI and ML driven applications, supporting models from traditional algorithms to NLP, protein language models, and large language models.
Build and maintain ML platform capabilities including data pipelines and feature engineering workflows.
Develop and maintain model training, evaluation, and deployment pipelines within the ML platform.
Develop and maintain experiment tracking and model registry systems.
Develop and maintain model performance evaluation and monitoring processes.
Partner to implement AI and ML Ops best practices, including CI/CD, infrastructure as code, monitoring, traceability, and reproducibility.
Collaborate with cross-functional teams to move experimentation outcomes into production-grade enterprise solutions.
Design and sustain 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 (or equivalent) required.
Bachelor’s degree with 2 years of experience in Computer Science, IT, or engineering field.
Associate’s degree with 6 years in Computer Science, IT, or engineering field.
High school diploma or GED with 8 years in Computer Science, IT, or engineering field.
Proficiency in software development with Python, version control, and test driven development.
Experience with cloud technologies, AWS preferred and Databricks familiarity.
Hands-on experience training and serving AI/ML models.

Technologies

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

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.

Application details

Application deadline: Amgen does not have a fixed deadline; applications accepted until the position is filled.
Sponsorship: Sponsorship for this role is not guaranteed.

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2d ago

Machine Learning Engineer

Intone Networks Remote 🌍 Remote

Remote

2d ago

Full time Ai Ml Artificial Intelligence Automation

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Job Description

Join Intone Networks in a remote capacity and collaborate with a distributed team to design, optimize, and sustain scalable ML pipelines. In this role you will partner with data scientists, engineers, and cross-functional colleagues to deploy production-grade models with robust CI/CD, while fostering a culture of collaboration and continuous improvement.

Responsibilities

Architect and productionize robust machine learning pipelines in a fast-moving environment.
Collaborate with data scientists, software engineers, and cross-functional partners to translate research models into dependable production systems.
Own the full ML lifecycle from data ingestion and feature engineering to training, deployment, monitoring, and iterative refinement.
Establish and sustain CI/CD workflows for ML applications to enable rapid, reliable releases.
Diagnose 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

Proven Python expertise with hands-on experience building production-grade ML applications.
Demonstrated ability to collaborate effectively in team settings with tight deadlines and complex technical challenges.
Solid understanding of MLOps best practices.
Experience containerizing applications with Docker.
Proficiency with Git and version-control workflows, including GitHub Actions.
Strong problem-solving skills and a collaborative, team-first mindset.

Technologies

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

Preferred Qualifications

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.

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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 seeks a Machine Learning Engineer to join its autonomous vehicle team in Austin, TX (onsite), focusing on motion planning and prediction, building end-to-end ML models, data pipelines, and real-time inference on embedded hardware.

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 data
Leverage transformer-based architectures to model complex temporal interactions among traffic agents
Define and own model performance metrics, and develop evaluation frameworks aligned with on-road safety and effectiveness
Collaborate with software engineers to integrate and optimize models for real-time onboard inference on embedded hardware
Stay current with advances in ML, imitation learning, and reinforcement learning, applying novel techniques to our systems

Requirements

Proficiency in Python with hands-on experience using modern deep learning frameworks such as PyTorch, TensorFlow, or JAX
Solid understanding of ML fundamentals, including neural networks, training methodologies, and evaluation techniques
Experience across the full ML lifecycle—from data exploration and prototyping to deployment and monitoring
C++ proficiency for high-performance model inference code

Technologies

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

Nice to Have

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

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