Machine Learning Infrastructure Engineer
Company: Unreal Gigs
Location: San Francisco
Posted on: May 8, 2024
Job Description:
Company Overview: Welcome to the forefront of machine learning
infrastructure! At our company, we're passionate about pushing the
boundaries of artificial intelligence and machine learning. Our
mission is to develop robust and scalable infrastructure solutions
that empower data scientists and machine learning engineers to
build, deploy, and manage cutting-edge machine learning models.
Join us and be part of a dynamic team committed to shaping the
future of machine learning infrastructure.
Position Overview: As a Machine Learning Infrastructure Engineer,
you'll play a crucial role in designing, building, and optimizing
our machine learning infrastructure to support the needs of our
organization. Working closely with cross-functional teams of data
scientists, software engineers, and DevOps specialists, you'll
ensure the reliability, scalability, and efficiency of our machine
learning systems. If you're passionate about machine learning
infrastructure and eager to drive innovation in AI, we want you on
our team.
Requirements
Key Responsibilities:
- Machine Learning Infrastructure Design: Design and architect
scalable and reliable infrastructure solutions to support machine
learning model development, training, and deployment.
- Model Training and Experimentation: Develop and maintain
infrastructure for model training and experimentation, including
distributed computing environments and GPU clusters.
- Model Deployment and Serving: Implement and manage
infrastructure for deploying and serving machine learning models in
production environments, ensuring low-latency and high
availability.
- Model Monitoring and Management: Develop monitoring and
management tools for tracking model performance, health, and drift,
and automating model retraining and redeployment.
- Data Processing and Feature Engineering: Develop pipelines and
tools for data processing, feature engineering, and preprocessing
to support machine learning model development.
- Infrastructure Automation: Implement infrastructure automation
and orchestration using tools such as Kubernetes, Docker,
Terraform, and Ansible to streamline deployment and management
processes.
- Performance Optimization: Optimize infrastructure performance
for speed, scalability, and cost-effectiveness, leveraging cloud
services and distributed computing technologies.
- Security and Compliance: Implement security controls and
compliance measures to protect sensitive data and ensure compliance
with regulatory requirements in machine learning workflows.
Qualifications:
- Bachelor's degree or higher in Computer Science, Engineering,
or related field.
- Strong background in infrastructure engineering, with hands-on
experience in designing, building, and optimizing infrastructure
solutions for machine learning.
- Proficiency in programming languages such as Python, Java, or
Go, and experience with machine learning frameworks such as
TensorFlow, PyTorch, or scikit-learn.
- Experience with cloud platforms such as AWS, Google Cloud
Platform, or Microsoft Azure, and familiarity with cloud services
for machine learning (e.g., SageMaker, AI Platform, Azure ML).
- Knowledge of distributed computing technologies such as Apache
Spark, Hadoop, or Dask, and experience with containerization and
orchestration technologies such as Docker and Kubernetes.
- Strong problem-solving abilities and analytical thinking, with
a keen attention to detail and a passion for tackling complex
technical challenges.
- Excellent communication and collaboration skills, with the
ability to work effectively in cross-functional teams and
communicate technical concepts to non-technical stakeholders.
Benefits
- Competitive salary: The industry standard salary for Machine
Learning Infrastructure Engineers typically ranges from $150,000 to
$230,000 per year, depending on experience and qualifications.
Exceptional candidates may be eligible for higher compensation
packages.
- Comprehensive health, dental, and vision insurance plans.
- Flexible work hours and remote work options.
- Generous vacation and paid time off.
- Professional development opportunities, including access to
training programs, conferences, and workshops.
- State-of-the-art technology environment with access to
cutting-edge tools and resources.
- Vibrant and inclusive company culture with team-building
activities and social events.
- Opportunities for career growth and advancement within the
company.
- Exciting projects with real-world impact in the field of
artificial intelligence and machine learning.
- Chance to work alongside top talent and industry experts in
machine learning infrastructure.
Join Us: Ready to shape the future of machine learning
infrastructure? Apply now to join our team and be part of an
exciting journey of innovation and discovery!
Keywords: Unreal Gigs, San Rafael , Machine Learning Infrastructure Engineer, Engineering , San Francisco, California
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