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Distillery Internships Jobs in California (NOW HIRING)

Atoms

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

Responsibilities : • Research and develop cutting edge RL and distillation techniques for ... Required : • 4+ years of non-internship professional MLE experience. • Deep expertise in ...

Atoms

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

Responsibilities : • Research and develop cutting edge RL and distillation techniques for ... Required : • 4+ years of non-internship professional MLE experience. • Deep expertise in ...

Meta

Research Scientist - Reality Labs

Sunnyvale, CA

$184K/yr

Proven track record of architecting knowledge distillation (KD) pipelines to compress frontier LLMs ... Demonstrated software engineering experience via internship, work experience, or widely used ...

Atoms

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

Responsibilities : • Research and develop cutting edge RL and distillation techniques for ... Required : • 4+ years of non-internship professional MLE experience. • Deep expertise in ...

Waabi

Research Scientist, World Models

San Francisco, CA · On-site +1

$155K - $269K/yr

... interns; foster a culture of scientific rigor and rapid experimentation. - Stay on top of emerging advances in generative AI, differentiable rendering, knowledge distillation/compression, and ...

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Distillery Internships information

What are the key skills and qualifications needed to thrive as a distillery intern, and why are they important?

To thrive as a Distillery Intern, you need a basic understanding of chemistry or food science, attention to detail, and a keen interest in the beverage industry, often supported by relevant coursework or experience. Familiarity with laboratory equipment, fermentation processes, and safety protocols is typically expected, and some positions may require knowledge of data recording or specific distillation software. Strong teamwork, communication skills, and a willingness to learn help you stand out in this hands-on, collaborative environment. These skills ensure product quality, adherence to safety standards, and effective support of production teams in a dynamic distillery setting.

What types of hands-on experience can I expect during a distillery internship?

As a distillery intern, you can expect to gain hands-on experience in various aspects of spirit production, such as fermentation, distillation, quality control, and bottling. You may assist in monitoring fermentation tanks, learning about raw ingredient selection, maintaining equipment, and supporting daily operations alongside experienced distillers. Interns often collaborate with both production and quality assurance teams, which provides a comprehensive understanding of the entire process. This immersive experience is valuable for those considering a long-term career in the beverage or spirits industry.

What is a distillery internship?

Distillery internships are temporary positions offered by distilleries to students or aspiring professionals who want to gain hands-on experience in the spirits industry. Interns typically assist with various tasks such as production, bottling, quality control, and sometimes marketing or event support. These internships provide practical knowledge of the distillation process, exposure to industry standards, and networking opportunities. They can be an important stepping stone for those interested in a career in beverage production or spirits management.

What is the difference between Distillery Internships vs Distillery Assistant?

AspectDistillery InternshipsDistillery Assistant
Required CredentialsHigh school diploma or ongoing college education, some technical knowledgeHigh school diploma, relevant experience preferred
Work EnvironmentHands-on, educational setting within distilleries, often seasonalFull-time or part-time work in distillery operations
Employer & Industry UsageInternships offered by distilleries for training and educationEntry-level role assisting with production and maintenance

Distillery Internships are primarily educational opportunities for students or individuals seeking industry experience, often seasonal and focused on learning. In contrast, Distillery Assistants are entry-level employees involved in daily production tasks, requiring some experience but offering more hands-on work. Both roles are essential in the distillery industry but serve different purposes in career development and operational support.

What are popular job titles related to Distillery Internships jobs in California? For Distillery Internships jobs in California, the most frequently searched job titles are:
What job categories do people searching Distillery Internships jobs in California look for? The top searched job categories for Distillery Internships jobs in California are:
What cities in California are hiring for Distillery Internships jobs? Cities in California with the most Distillery Internships job openings:
Distillery Internships jobs near you
Infographic showing various Distillery Internships job openings in California as of August 2026, with employment types broken down into 14% Internship, 1% As Needed, 68% Full Time, 14% Part Time, 2% Temporary, and 1% Contract. Highlights an 92% Physical, 5% Hybrid, and 3% Remote job distribution.

AI Engineer, Internship - Summer 2026 - Applications Open Now

Postman

Berkeley, CA

Temporary, Internship

Posted 9 days ago

Job description

The Opportunity (Summer 2026 AI Internship - Applications Open Now)

We're seeking an AI Engineer Intern to work alongside our AI team on large-scale AI and Agentic  systems from data pipeline to production deployment. This role is scoped for someone with foundational experience who wants to deepen it: you'll own discrete pieces of real systems under the mentorship of senior engineers, not shadow work or isolated coursework-style projects.

What You'll Do

You'll work directly with the AI team, taking responsibility for well-scoped pieces of real systems, with mentorship from senior engineers.

Benchmarks & Evaluation

  • Contribute to APIFlow-Bench, our open-source benchmark for real API-development work: design and review benchmark tasks and their mock API environments, extend the evaluation harness and task-generation pipeline in Python, and help maintain the public multi-model leaderboard with statistical confidence intervals.
  • Help build a new action-level AI safety benchmark: instead of grading what a model says, it scores what an agent actually does inside a simulated enterprise API environment. You'll work on scenario design, threat modeling (prompt injection, data exfiltration, permission overreach), and auditable evaluation design.

Model Training & Efficiency

  • Fine-tune open-weight models for tool calling and agentic tasks (SFT, distillation, and RL) using PyTorch and the open-source training ecosystem, on both managed training platforms and self-managed cloud GPUs.
  • Design and run experiments with rigor: evaluate every training run on our benchmarks, support ablation studies and error analysis, track experiments, and report results honestly, including cost.
  • Evaluate ultra-low-bit quantized models for on-device use: extend our quantized vs. full-precision benchmark comparisons and analyze where and why they diverge.

Agent Systems & Engineering Practice

  • Help build the next generation of Postman's in-product AI agent (Agent Mode): a deliberately minimal agent architecture that calls LLM APIs directly (tool loops, multi-step execution, checkpointing), primarily in TypeScript. No prior TypeScript is required; strong Python fundamentals transfer quickly.
  • Read the source code of open-source agent harnesses and turn what you learn into design specs and prototypes.
  • Document experiments, design decisions, and runbooks so your work is legible to the next person; flag safety, fairness, or privacy concerns you observe in model or agent behavior.
About You
  • Currently pursuing a BS, MS, or PhD in Computer Science, Data Science, or a related quantitative field.
  • Hands-on experience training or evaluating ML models: course projects, research, hackathons, or a prior internship all count.
  • Solid Python fundamentals: data structures, functions, basic testing; comfortable writing and reviewing code outside of notebooks.
  • Working knowledge of at least one deep-learning framework (PyTorch preferred).
  • Clear written and verbal communication, and a habit of documenting what you build.
Preferred Qualifications  (none required; the more of these you have, the better)
  • Experience fine-tuning open-weight LLMs (SFT, LoRA, RL, or distillation), with the improvement measured on a benchmark.
  • Experience building LLM agents (tool calling, multi-step loops) or LLM evaluation harnesses/benchmarks, and reporting results with statistical rigor.
  • A track record of shipping real software end-to-end: APIs and services, CLIs, Docker, CI/CD, cloud; public code on GitHub is a big plus.
  • Interest or experience in AI safety and robustness: red-teaming, prompt injection, agent security, fairness, or interpretability.
  • Exposure to model-efficiency work: quantization, low-bit inference, or serving optimization.
  • Evidence of rigor and initiative: publications, technical blog posts, ablation studies, or self-driven side projects with quantified results.
  • Fluency with AI coding tools (Claude Code, Cursor, Codex) to ship fast while still deeply understanding the systems you build.

Apply