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3 jobs found

1d ago

Machine Learning Engineer

Amgen Remote 🇺🇸 Remote

Remote

1d ago

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

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Job Description

Amgen offers a remote-friendly environment in the United States with a supportive, collaborative culture and a strong focus on growth. You will join a team that backs scientist-driven work with scalable ML platforms, comprehensive benefits, stock-based incentives, and generous time off. The role emphasizes flexible work models, professional development, and a mission to advance treatments for patients living with serious illnesses.

Benefits

Retirement and Savings Plan with generous company contributions, plus group medical, dental, and vision coverage
Life and disability insurance and flexible spending accounts
Discretionary annual bonus program (or field sales incentive plan where applicable)
Stock-based long-term incentives
Award-winning time-off plans
Flexible work models where possible

What you will do

In this role you will contribute to the development of scalable machine learning platforms and workflows that enable scientists and researchers at Amgen to build, deploy, and manage AI and ML models. You will collaborate with experienced engineers, data scientists, and domain experts to productionize ML solutions that primarily support drug discovery and development. This position is designed for engineers at an early to mid stage in their ML engineering career, with opportunities to grow alongside a talented team.

Responsibilities

Deliver AI and ML enabled applications with deployed models spanning classical ML, natural language processing, protein language models, and large language models
Develop and maintain ML platform capabilities including data pipelines and feature engineering workflows
Develop and maintain model training, evaluation, and deployment pipelines
Maintain experiment tracking and model registry systems
Maintain model performance evaluations and monitoring
Implement AI and ML Ops best practices, including CI/CD, infrastructure as code, monitoring, traceability and reproducibility
Collaborate with cross-functional teams to transition from experimentation to 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 field
Associate’s degree and 6 years in Computer Science, IT, or engineering field
High school diploma or GED and 8 years in Computer Science, IT, or engineering field
Software programming experience in Python, version control, and 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

Details

Location: Remote (remote)
Salary: USD 129,654 - 175,415 per yearly

Sponsorship

Sponsorship for this role is not guaranteed.

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1d ago

Machine Learning Engineer

Intone Networks Remote 🌍 Remote

Remote

1d ago

Full time Ai Ml Artificial Intelligence Automation

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Job Description

Work remotely with a collaborative, high‑performing team at Intone Networks. This role focuses on building, optimizing, and maintaining scalable ML pipelines and systems, partnering with data scientists, engineers, and cross‑functional colleagues to deploy production‑grade models with robust CI/CD. You will own the end‑to‑end ML lifecycle and contribute to a culture that emphasizes clear communication and proactive problem solving.

Responsibilities

Design, develop, and productionize robust machine learning pipelines in a fast paced setting.
Work closely with data scientists, engineers, and cross‑functional teams to turn models into reliable, scalable production systems.
Own end‑to‑end aspects of the ML lifecycle, including data ingestion, feature engineering, model training, deployment, monitoring, and iteration.
Build and maintain CI/CD workflows for ML systems to support fast and reliable releases.
Troubleshoot and optimize complex pipeline issues to meet tight deadlines.
Foster a positive, high‑performing team culture through clear communication, knowledge sharing, and proactive problem solving.

Requirements

Strong Python expertise with hands‑on experience building production‑grade ML applications.
Proven ability to collaborate effectively within a team facing tight deadlines and complex technical challenges.
Solid understanding of MLOps best practices.
Experience with containerization using 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, especially Datadog.
Background 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 is seeking a Machine Learning Engineer to join its autonomous vehicle team in Austin, TX on site, focusing on motion planning and prediction. The role entails building end-to-end ML models, developing data pipelines, and enabling real-time inference on embedded hardware, while applying cutting-edge ML research.

Responsibilities

Develop and operationalize advanced machine learning models for behavioral prediction and motion planning
Build scalable data pipelines to process, clean, and label large-scale vehicle sensor and simulation datasets
Leverage architectures such as transformers to capture temporal interactions among traffic agents
Define and own model performance metrics and create evaluation frameworks aligned with on-road safety and performance
Collaborate with software engineers to integrate models and optimize real-time inference on embedded vehicle hardware
Maintain awareness of the latest ML research, including imitation learning and reinforcement learning, and apply novel techniques to systems

Requirements

Proficient in Python with hands-on experience in modern deep learning frameworks (PyTorch, TensorFlow, or JAX)
Solid understanding of ML fundamentals, including neural network architectures, training methodologies, and evaluation techniques
Experience across the full ML lifecycle, from data exploration and prototyping to deployment and monitoring
C++ proficiency for writing 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 (for example Kaggle) or contributions to major open-source ML projects
Experience applying ML to robotics problems, such as behavioral prediction, motion planning, or computer vision
Familiarity with MLOps tools and platforms (MLflow, Kubeflow, Weights & Biases)
Experience with large-scale distributed data processing and training frameworks (Spark, Ray)
Publications in top-tier ML or robotics conferences (NeurIPS, ICML, CVPR, ICLR, CoRL, RSS)

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