Research Intern - LLM Performance Optimization Job at Microsoft Corporation (Redmond)

PhD AI Research Intern

Join our cutting-edge Machine Learning Research team at Atlassian as a PhD Resea...

Location

Canada

Salary:

55.00 USD / Hour

Atlassian

Expiration Date

Until further notice

Requirements

Completed Bachelors degree in Computer Science or a related field
Currently pursuing a PhD in Computer Science or a related field at any stage of your doctoral studies
Strong foundation in AI/ML, LLMs, modeling and/or optimization techniques

Job Responsibility

Collaborate cross-functionally with Research Scientists and Machine Learning Engineers to design, implement, and evaluate experiments that advance the performance, efficiency, and scalability of modern ML and LLM systems for our AI products
Curate, preprocess, and manage large-scale datasets for training and evaluation, ensuring data quality, diversity, and reproducibility across experiments
Conduct continued training, fine-tuning, and alignment of large language models for specialized applications such as conversational AI, summarization, generative search, and multimodal agents
Evaluate cutting-edge ML algorithms through rigorous experimentation and provide detailed analyses highlighting performance insights, failure modes, and opportunities for improvement
Contribute to publications and presentations at internal workshops or top-tier academic venues, helping to drive innovation in Enterprise AI and large-scale ML systems

What we offer

health and wellbeing resources
paid volunteer days

PhD AI Research Intern

Join our cutting-edge Machine Learning Research team at Atlassian as a PhD Resea...

Location

United States , Seattle

Salary:

49.00 - 75.00 USD / Hour

Atlassian

Expiration Date

Until further notice

Requirements

Completed Bachelors degree in Computer Science or a related field
Currently pursuing a PhD in Computer Science or a related field at any stage of your doctoral studies
Degree completion date cannot be earlier than September 2026 - June 2027
Strong foundation in AI/ML, LLMs, modeling and/or optimization techniques
Exhibit a solid grasp of algorithms and data structures
Demonstrate proficiency in Python programming and ability to write clean, efficient, and well-documented code
Experience working with large-scale datasets, including data preprocessing, augmentation, and scaling techniques
Has expertise in managing data using Python libraries such as NumPy, Pandas, Matplotlib, in addition to leveraging models from Hugging Face and has practical knowledge of applied machine learning and deep learning frameworks, like PyTorch
Demonstrated exposure to natural language processing (NLP) and Computer Vision (CV)
Familiarity with state-of-the-art research in machine learning and AI, as evidenced by relevant coursework, publications, or projects

Job Responsibility

Collaborate cross-functionally with Research Scientists and Machine Learning Engineers to design, implement, and evaluate experiments that advance the performance, efficiency, and scalability of modern ML and LLM systems for our AI products
Curate, preprocess, and manage large-scale datasets for training and evaluation, ensuring data quality, diversity, and reproducibility across experiments
Conduct continued training, fine-tuning, and alignment of large language models for specialized applications such as conversational AI, summarization, generative search, and multimodal agents
Evaluate cutting-edge ML algorithms through rigorous experimentation and provide detailed analyses highlighting performance insights, failure modes, and opportunities for improvement
Contribute to publications and presentations at internal workshops or top-tier academic venues, helping to drive innovation in Enterprise AI and large-scale ML systems

What we offer

health and wellbeing resources
paid volunteer days

Master’s research intern

Automated Prompt Optimization for Industrial Applications Based on LLMs. As part...

Location

France , Hem

Salary:

Not provided

Hornetsecurity

Expiration Date

Until further notice

Requirements

Master’s student (or equivalent) in Computer Science, Artificial Intelligence, Machine Learning, or a related field, ideally with a research component
Strong interest in LLM prompt engineering and evaluation methodologies
Proficient in Python and modern machine learning tools
Research-oriented mindset, capable of critically reading and analyzing recent scientific papers, formulating hypotheses and designing experiments to test them
Willingness to pursue a CIFRE PhD after the internship
Intellectually curious, autonomous, and rigorous, able to document work clearly and communicate results to both technical and non-technical audiences
Located in Paris or Lille
Fluent in English (written and spoken)

Job Responsibility

Designing and evaluating an automated prompt optimization pipeline using frameworks such as DSPy
Exploring the state-of-the-art in prompting and optimization techniques
Implementing automated prompt optimization using open-source tools
Defining and tracking performance metrics (accuracy, recall, F1)
Extending evaluation with text quality metrics (fluency, correctness, faithfulness, etc.)
Integrating quality feedback through “LLM-as-a-judge” methods into the optimization loop

What we offer

100% reimbursement of public transportation costs
Meal vouchers worth €10 per working day
CSE benefits & Student health insurance providing effective coverage from day one

Fulltime

Research Scientist Intern, PyTorch Distributed

Meta is seeking a Research Scientist Intern to join our Meta PyTorch Distributed...

Location

United States , Menlo Park

Salary:

7650.00 - 12134.00 USD / Month

Technical Program Manager, Platform

As a Technical Program Manager for the Platform team, you will partner with engi...

Location

United States , San Francisco, CA; New York, NY

Salary:

211200.00 - 264000.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

5+ years of experience as a Technical Program Manager, Product Manager, or Software Engineer, with a proven track record of having built and shipped technical products or platforms from scratch (e.g., internal cloud infrastructure, developer APIs, distributed systems, or ML platforms)
Platform Domain Expertise: 3+ years of dedicated experience managing programs focused directly on core engineering infrastructure, cloud-native ecosystems (AWS/GCP), container orchestration (Kubernetes), or distributed systems
AI/ML Infrastructure Literacy: Foundational understanding of the infrastructure required for the Generative AI lifecycle, including high-throughput data pipelines, GPU/CPU cluster utilization, or model training/evaluation setups
Masterful Communication: Proven track record of presenting to and influencing executive-level stakeholders, with the ability to translate complex technical/architectural challenges into clear business impacts
Execution Excellence: Advanced proficiency with iterative development methodologies and modern project management tooling (Linear, Jira, etc.) applied to foundational infrastructure environments.

Job Responsibility

Lifecycle & Platform Delivery: Lead strategic planning and high-velocity execution for SGP core capabilities (orchestration layers, model serving, APIs). Manage features from technical scoping and architecture design through production launch
Cross-Functional GenAI Alignment: Drive execution and manage complex technical dependencies across systems engineering, Core ML, Research, and Product teams to deliver unified SGP capabilities with architectural consistency
Technical Translation & Requirements: Translate complex infrastructure metrics (LLM inference optimization, GPU utilization, compute orchestration) into actionable roadmaps. Map demands like multi-tenancy, data privacy, and isolation into platform features
Risk & Dependency Mitigation: Proactively identify, track, and mitigate technical risks unique to massive-scale GenAI infrastructure and global SGP deployments, maintaining momentum despite fast-evolving AI frameworks
Developer Velocity & Operational Excellence: Establish lightweight agile processes that empower engineers to ship fast without breaking core systems. Define and enforce clear SLOs and performance benchmarks to guarantee production-grade reliability for clients
Metrics-Driven Adoption: Track and report on SGP adoption metrics, system reliability, delivery forecasts, and engineering bottlenecks directly to executive leadership to ensure the platform scales responsibly.

What we offer

comprehensive health, dental and vision coverage
retirement benefits
a learning and development stipend
generous PTO
commuter stipend

Fulltime

AI Machine Learning Scientist

The AI Machine Learning Scientist plays a critical role in enabling the responsi...

Location

United States , Richmond; Tampa; Atlanta; Indianapolis

Salary:

Not provided

Elevance Health

Expiration Date

June 26, 2026

Requirements

Requires a Bachelor’s degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent degree and 4 or more years of experience
or any combination of education and experience in configuration management, which would provide an equivalent background.

Job Responsibility

Design, develop, and deploy AI/ML and Generative AI solutions that address business and operational challenges at enterprise scale
Develops and maintains infrastructure systems that connect internal data sets
creates new data collection frameworks for structured and unstructured data
Develop reusable AI capabilities including RAG pipelines, vector search, semantic retrieval, prompt orchestration, and agentic workflows
Implement evaluation frameworks and automated testing strategies to measure model quality, accuracy, bias, safety, and performance
Establish monitoring, observability, and governance processes to ensure AI systems remain reliable and compliant in production
Drive adoption of Responsible AI practices by implementing evaluation standards, audit-ready documentation, and model governance controls
Optimize AI systems for scalability, latency, reliability, and cost efficiency.

What we offer

Merit increases
paid holidays
Paid Time Off
incentive bonus programs
medical, dental, vision, short and long term disability benefits
401(k) +match
stock purchase plan
life insurance
wellness programs
financial education resources

Fulltime

!

Senior Ml Engineer

Location

Colombia , Medellín, Antioquia;Bogotá, Capital District;Cali, Valle del Cauca;Barranquilla;Bucaramanga, Santander

Salary:

Not provided

Provectus

Expiration Date

Until further notice

Requirements

ML Fundamentals: supervised, unsupervised, and reinforcement learning
Model Development: feature engineering, model training, evaluation, hyperparameter tuning, and validation
ML Frameworks: classical ML libraries, TensorFlow, PyTorch, or similar frameworks
Deep Learning: CNNs, RNNs, Transformers
LLM Applications: Experience building production LLM-based applications
Prompt Engineering: Ability to design effective prompts and chain-of-thought strategies
RAG Systems: Experience building retrieval-augmented generation architectures
Vector Databases: Familiarity with embedding models and vector search
LLM Evaluation: Experience with evaluation metrics and techniques for LLM outputs
Python: Advanced proficiency in Python for ML applications

Job Responsibility

Design and implement end-to-end ML solutions from experimentation to production
Build scalable ML pipelines and infrastructure
Optimize model performance, efficiency, and reliability
Write clean, maintainable, production-quality code
Conduct rigorous experimentation and model evaluation
Troubleshoot and resolve complex technical challenges
Mentor junior and mid-level ML engineers
Conduct code reviews and provide constructive feedback
Share knowledge through documentation, presentations, and workshops
Collaborate with cross-functional teams (DevOps, Data Engineering, SAs)

What we offer

Long-term B2B collaboration
Fully remote setup
A budget for your medical insurance
Paid sick leave, vacation, public holidays
Continuous learning support, including unlimited AWS certification sponsorship

Fulltime

Senior ML Engineer (GenAI, AWS)

Provectus helps companies adopt ML/AI to transform the ways they operate, compet...

Location

Colombia , Medellín; Bogotá; Cali; Barranquilla; Bucaramanga

Salary:

Not provided

Provectus

Expiration Date

Until further notice

Requirements

ML Fundamentals: supervised, unsupervised, and reinforcement learning
Model Development: feature engineering, model training, evaluation, hyperparameter tuning, and validation
ML Frameworks: classical ML libraries, TensorFlow, PyTorch, or similar frameworks
Deep Learning: CNNs, RNNs, Transformers
LLM Applications: Experience building production LLM-based applications
Prompt Engineering: Ability to design effective prompts and chain-of-thought strategies
RAG Systems: Experience building retrieval-augmented generation architectures
Vector Databases: Familiarity with embedding models and vector search
LLM Evaluation: Experience with evaluation metrics and techniques for LLM outputs
Python: Advanced proficiency in Python for ML applications

Job Responsibility

Design and implement end-to-end ML solutions from experimentation to production
Build scalable ML pipelines and infrastructure
Optimize model performance, efficiency, and reliability
Write clean, maintainable, production-quality code
Conduct rigorous experimentation and model evaluation
Troubleshoot and resolve complex technical challenges
Mentor junior and mid-level ML engineers
Conduct code reviews and provide constructive feedback
Share knowledge through documentation, presentations, and workshops
Collaborate with cross-functional teams (DevOps, Data Engineering, SAs)

What we offer

Long-term B2B collaboration
Fully remote setup
A budget for your medical insurance
Paid sick leave, vacation, public holidays
Continuous learning support, including unlimited AWS certification sponsorship

Fulltime

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Research Intern - LLM Performance Optimization

Job Description

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