Machine Learning Engineering Graduate Intern

Jobtailor

California (MO)

On-site

USD 34,000 - 48,000

Full time

3 days ago

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Job summary

Jobtailor is seeking a motivated intern to develop and run machine learning experiments across NLP, computer vision, time series, and reinforcement learning.

You will evaluate models for scalable applications, collaborate with multidisciplinary teams, and present results to stakeholders while contributing to a culture of learning. This 10-week, full-time internship emphasizes hands-on ML work and teamwork.

Qualifications

Pursuing a Master’s or PhD in CS/CE; full-time enrollment.
Willing to commit 10 weeks full-time and return to degree program after completion.
Minimum GPA of 3.0.
Bachelor's degree completed by internship start.
Proficiency in Python with ML libraries (PyTorch).
Experience with Docker and Kubernetes.
Experience with ML/AI, software engineering and statistics.
Familiarity with MLOps concepts and tools (MLFlow, DVC).
Experience designing CV or NLP applications using ML models.
Experience using GPUs and NVIDIA tools.
Familiarity with Unix/Linux.
Cloud native development or microservice architectures.
Ability to obtain US security clearance; US citizenship.
Transcripts required.
GPA 3.5+ (impressive qualification); Active security clearance (impressive).
Familiarity with HPC hardware, CUDA programming and ML optimization techniques.
Experience with Slurm or GPU-enabled distributed ML training.
Experience building ML on edge/embedded hardware.
Experience with Hadoop, Spark, Flink.
Experience building scalable AI solutions for narrow use cases.

Responsibilities

Develop and run ML experiments across NLP, CV, time series, and RL.
Evaluate models for scalable, reliable applications.
Collaborate with multidisciplinary teams to deliver features.
Present results in written and verbal form to stakeholders.
Foster a learning mindset and progress within the team.
Work across organizational boundaries on projects.

Skills

Python

PyTorch

Docker

Kubernetes

MLOps

CUDA

Unix/Linux

Cloud

Distributed systems

HPC

Education

Pursuing Master's or PhD in CS/CE

Bachelor's degree by internship start

Tools

MLFlow

Data Version Control

NVIDIA Developer Tools

Hadoop

Spark

Flink

Slurm

Job description

Develop and execute machine learning and data science experiments in natural language processing, computer vision, time series analysis, reinforcement learning, and related domains
Evaluate technologies and data science models for scalable and resilient mission-critical applications
Collaborate with teams of various sizes to deliver features and products
Present written and verbal results to customer stakeholders
Reinforce an environment of learning and progress with team members and others
Work as part of multidisciplinary teams spanning experience levels and organizational boundaries

Requirements

Currently enrolled full-time in an accredited college/university program pursuing a Master's or PhD degree in Computer Science, Computer Engineering, or related discipline
Availability to work full-time for a minimum of 10 weeks outside of university term and ability to return to a Master's or PhD degree program full-time after completion of the internship
Minimum GPA of 3.0
Bachelor's degree completed by internship start date
Proficiency in Python, including major ML libraries and tools (PyTorch)
Experience with container orchestration tooling (Docker, Kubernetes, etc.)
Experience with and understanding of machine learning and artificial intelligence, software engineering, and statistics
Experience with software engineering concepts with an AI focus (MLOps/DevOps, ML Development Lifecycle, Scalable ML Architecture, etc.)
Familiarity with MLOps processes and tools (MLFlow, Data Version Control etc.)
Specific experience designing either computer vision or natural language processing applications leveraging ML models
Experience leveraging GPUs to scale and measure ML solution performance (NVIDIA developer tools etc.)
Familiarity with Unix/Linux operating systems
Experience with cloud native application development or cloud infrastructure and microservice architectures
Ability to obtain and maintain a U.S. government-issued security clearance
U.S. citizenship required to obtain a security clearance
Transcripts required
GPA 3.5 or higher (impressive qualification)
Active security clearance (impressive qualification)
Familiarity with high-performance computing hardware for ML, CUDA programming, and advanced ML optimization techniques and architectures (impressive qualification)
Experience with Slurm, Kubernetes, or other cluster job orchestration frameworks leveraging GPU resources to run distributed ML training jobs at scale (impressive qualification)
Experience building ML solutions on edge and embedded hardware (impressive qualification)
Experience with distributed and stream data processing and big data frameworks such as Hadoop, Spark, or Flink (impressive qualification)
Experience building scalable agentic and generative AI solutions for narrow-scoped use cases (impressive qualification)

Core Competencies

Demonstrates expertise in Machine Learning, Natural Language Processing, and Computer Vision, with proficiency in Python and major ML libraries. Capable of collaborating within multidisciplinary teams and presenting complex results to stakeholders.

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