What makes our work distinct is that we're engineering models specifically for Apple silicon and ... Distillation and alignment: on-policy distillation, reward-tilted distillation, cross-stage ...
What makes our work distinct is that we're engineering models specifically for Apple silicon and ... Distillation and alignment: on-policy distillation, reward-tilted distillation, cross-stage ...
Senior AI Engineer
Manhattan, NY · On-site
$200K - $300K/yr
Fine-tuning and model distillation to improve performance and efficiency * Real-time inference ... Hard science degrees (Physics/Math/Engineering) welcome with strong technical foundation
Senior AI Engineer
Manhattan, NY · On-site
$200K - $300K/yr
Fine-tuning and model distillation to improve performance and efficiency * Real-time inference ... Hard science degrees (Physics/Math/Engineering) welcome with strong technical foundation
Senior AI Engineer
$200K - $300K/yr
Fine-tuning and model distillation to improve performance and efficiency * Real-time inference ... Hard science degrees (Physics/Math/Engineering) welcome with strong technical foundation
Senior AI Engineer
$200K - $300K/yr
Fine-tuning and model distillation to improve performance and efficiency * Real-time inference ... Hard science degrees (Physics/Math/Engineering) welcome with strong technical foundation
ML Researcher, Apple Foundation Models
$184K - $324K/yr
What makes our work distinct is that we're engineering models specifically for Apple silicon and ... Distillation and alignment: on-policy distillation, reward-tilted distillation, cross-stage ...
ML Researcher, Apple Foundation Models
$184K - $324K/yr
What makes our work distinct is that we're engineering models specifically for Apple silicon and ... Distillation and alignment: on-policy distillation, reward-tilted distillation, cross-stage ...
Senior AI Engineer
New York, NY · On-site
$95K - $300K/yr
... engineering, and determine whether each intervention genuinely made the system better. Models and Learning * Apply methods such as fine-tuning, distillation, reinforcement learning, preference ...
Senior AI Engineer
New York, NY · On-site
$95K - $300K/yr
... engineering, and determine whether each intervention genuinely made the system better. Models and Learning * Apply methods such as fine-tuning, distillation, reinforcement learning, preference ...
Senior AI Engineer - Clinical Reasoning
Manhattan, NY · On-site
$115K - $158K/yr
Identify whether improvements should come from reasoning, retrieval, model behavior, data, or engineering changes * Apply methods such as fine-tuning, distillation, reinforcement learning, preference ...
Senior AI Engineer - Clinical Reasoning
Manhattan, NY · On-site
$115K - $158K/yr
Identify whether improvements should come from reasoning, retrieval, model behavior, data, or engineering changes * Apply methods such as fine-tuning, distillation, reinforcement learning, preference ...
Engineering Manager-Port Newark, NJ.
Newark, NJ · On-site
$170K - $185K/yr
... including reaction, distillation, extrusion, separation, and drying in a GMP environment ... Engineering management processes and CAPEX budget controls. The salary or hourly wage scale ...
Engineering Manager-Port Newark, NJ.
Newark, NJ · On-site
$170K - $185K/yr
... including reaction, distillation, extrusion, separation, and drying in a GMP environment ... Engineering management processes and CAPEX budget controls. The salary or hourly wage scale ...
Senior AI Engineer - Clinical Reasoning
$115K - $158K/yr
Identify whether improvements should come from reasoning, retrieval, model behavior, data, or engineering changes * Apply methods such as fine-tuning, distillation, reinforcement learning, preference ...
Senior AI Engineer - Clinical Reasoning
$115K - $158K/yr
Identify whether improvements should come from reasoning, retrieval, model behavior, data, or engineering changes * Apply methods such as fine-tuning, distillation, reinforcement learning, preference ...
Senior AI Engineer - Clinical Reasoning
$115K - $158K/yr
Identify whether improvements should come from reasoning, retrieval, model behavior, data, or engineering changes * Apply methods such as fine-tuning, distillation, reinforcement learning, preference ...
Quick apply
Senior AI Engineer - Clinical Reasoning
$115K - $158K/yr
Identify whether improvements should come from reasoning, retrieval, model behavior, data, or engineering changes * Apply methods such as fine-tuning, distillation, reinforcement learning, preference ...
... distillation (KD) pipelines to compress frontier LLMs into optimized edge models * Experience bringing LLM-based products from research to production * Demonstrated software engineering experience ...
... distillation (KD) pipelines to compress frontier LLMs into optimized edge models * Experience bringing LLM-based products from research to production * Demonstrated software engineering experience ...
Design and detail engineering of Pressure Vessels and Storage Tanks, including internals ... Rigging and Lifting analysis for vessels, distillation columns, and tanks Regular employees ...
Design and detail engineering of Pressure Vessels and Storage Tanks, including internals ... Rigging and Lifting analysis for vessels, distillation columns, and tanks Regular employees ...
QC Analyst
$26 - $31/hr
Perform laboratory-scale distillation of essential oils, natural products, and aromatic raw ... Bachelor's degree in Chemistry, Chemical Engineering, Biology, Food Science, or a related ...
QC Analyst
$26 - $31/hr
Perform laboratory-scale distillation of essential oils, natural products, and aromatic raw ... Bachelor's degree in Chemistry, Chemical Engineering, Biology, Food Science, or a related ...
Quantitative Software Engineer: Techniques Engineering
Manhattan, NY · On-site
$165 - $300/hr
... distillation, and intelligent batching * Continuously assess and fine-tune both research and ... Strong software engineering skills using Python, version control, testing frameworks, and CI/CD ...
Quantitative Software Engineer: Techniques Engineering
Manhattan, NY · On-site
$165 - $300/hr
... distillation, and intelligent batching * Continuously assess and fine-tune both research and ... Strong software engineering skills using Python, version control, testing frameworks, and CI/CD ...
Collaborate with cloud engineering teams on Terraform modules, IaC templates, environment promotion ... Adapt and optimize models using LoRA, PEFT, instruction tuning, distillation, transfer learning ...
Collaborate with cloud engineering teams on Terraform modules, IaC templates, environment promotion ... Adapt and optimize models using LoRA, PEFT, instruction tuning, distillation, transfer learning ...
Senior AI Engineer
$200K - $300K/yr
Partner with the agent engineering team to ensure the model layer meets agent workload Requirements: * 5+ years software engineering; strong Python * Production fine-tuning or distillation of open ...
Quick apply
Senior AI Engineer
$200K - $300K/yr
Partner with the agent engineering team to ensure the model layer meets agent workload Requirements: * 5+ years software engineering; strong Python * Production fine-tuning or distillation of open ...
GenAI Engineer; Machine Learning Engineer - LLM; AI Platform Engineer; NLP Engineer; Applied ML ... Adapt and optimize models using LoRA, PEFT, instruction tuning, distillation, transfer learning ...
GenAI Engineer; Machine Learning Engineer - LLM; AI Platform Engineer; NLP Engineer; Applied ML ... Adapt and optimize models using LoRA, PEFT, instruction tuning, distillation, transfer learning ...
Collaborate with cloud engineering teams on Terraform modules, IaC templates, environment promotion ... Adapt and optimize models using LoRA, PEFT, instruction tuning, distillation, transfer learning ...
Collaborate with cloud engineering teams on Terraform modules, IaC templates, environment promotion ... Adapt and optimize models using LoRA, PEFT, instruction tuning, distillation, transfer learning ...
Staff Machine Learning Engineer, Personalization
Manhattan, NY · On-site
$227.49 - $324.99/hr
As a Staff Machine Learning Engineer, you will help shape the future of personalized discovery and ... SFT), distillation, and parameter-efficient training approaches. * Partner closely with product ...
Staff Machine Learning Engineer, Personalization
Manhattan, NY · On-site
$227.49 - $324.99/hr
As a Staff Machine Learning Engineer, you will help shape the future of personalized discovery and ... SFT), distillation, and parameter-efficient training approaches. * Partner closely with product ...
Senior Applied Scientist, Document Understanding
New York, NY · On-site +1
$100K - $136K/yr
Apply knowledge distillation techniques to compress large models into latency-constrained ... Partner with engineering on delivery, reliability, and scale across multiple product lines
Senior Applied Scientist, Document Understanding
New York, NY · On-site +1
$100K - $136K/yr
Apply knowledge distillation techniques to compress large models into latency-constrained ... Partner with engineering on delivery, reliability, and scale across multiple product lines
Staff ML Engineer, Personalization & Moments Discovery
Manhattan, NY · On-site
$227K - $324K/yr
... SFT), distillation, and parameter-efficient training approaches. Partner closely with product ... Machine Learning Engineering Manager, Personalization Senior Machine Learning Engineer ...
Staff ML Engineer, Personalization & Moments Discovery
Manhattan, NY · On-site
$227K - $324K/yr
... SFT), distillation, and parameter-efficient training approaches. Partner closely with product ... Machine Learning Engineering Manager, Personalization Senior Machine Learning Engineer ...
Distillery Engineering information
What are some typical challenges faced by professionals in distillery engineering roles?
Distillery engineers often work with complex systems where even minor production issues can impact product quality, yield, and safety, so troubleshooting and quick decision-making are daily challenges. The role frequently involves coordinating with cross-functional teams—including operators, quality control specialists, and maintenance crews—to implement process improvements and ensure seamless production. Additionally, engineers must stay current with evolving regulations and sustainability practices, which can add layers of complexity to project management. Embracing these challenges is key to driving innovation and maintaining high standards in the distilling industry.
What is distillery engineering?
A Distillery Engineering job involves designing, maintaining, and optimizing the equipment and processes used in alcohol production. Engineers in this field work with fermentation, distillation, and bottling systems to ensure efficiency, safety, and product quality. They may also focus on energy efficiency, automation, and regulatory compliance. This role requires expertise in mechanical, chemical, or process engineering, along with a strong understanding of brewing and distillation principles.
What are the key skills and qualifications needed to thrive in distillery engineering, and why are they important?
To thrive in Distillery Engineering, a strong background in chemical, mechanical, or process engineering with knowledge of distillation processes and safety regulations is essential. Familiarity with process control systems, automation software, quality assurance practices, and relevant industry certifications like OSHA or Six Sigma is highly valued. Excellent problem-solving abilities, teamwork, and clear communication are important soft skills for this role. These skills ensure efficient, safe, and innovative operations in the production of distilled spirits, supporting both quality and regulatory compliance.
What are popular job titles related to Distillery Engineering jobs in New York?
For Distillery Engineering jobs in New York, the most frequently searched job titles are:
What job categories do people searching Distillery Engineering jobs in New York look for?
The top searched job categories for Distillery Engineering jobs in New York are:
Apple rating
8.0
Based on 677 frontline employees who took The Breakroom Quiz
7th of 30 rated technology retailers
Job description
We build frontier foundation models that power intelligent experiences at Apple. Our team works across the full training lifecycle: including pre-training foundation models, and developing mid-training approaches that bridge general capability and task-specific performance. What makes our work distinct is that we're engineering models specifically for Apple silicon and optimized for experiences that are private, personal, and deeply integrated into the OS. We're solving frontier problems in reward modeling to resist reward hacking, handling sparse and delayed rewards in agentic settings, and aligning models reliably across the spectrum from open-ended creative tasks to precise, action-taking workflows. If you're drawn to hard problems where the research and the product are inseparable, this is the team
Description
We are building the next generation of models optimized for Agentic, Reasoning, and Coding capabilities. This means training models via RL to reason from first principles, building autonomous coding agents that operate in real repositories, and developing agentic systems that handle multi-step workflows with error recovery. You will work on problems like: RL with verifiable rewards for mathematical reasoning, multi-turn RL for coding agents evaluated on SWE-Bench and beyond, scaling laws for RL compute allocation, progressive alignment across capability stages, and training models to manage their own context in long-horizon tasks. This is applied research with direct product impact - your work will ship to millions of users.
Minimum Qualifications
Demonstrated expertise in deep learning with publications at top ML or NLP conferences, or a track record of applying deep learning techniques to products
Proficient programming skills in Python and one of the deep learning toolkits such as JAX, PyTorch, or Tensorflow
Ability to work in a collaborative environment.
PhD, or equivalent practical experience, in Computer Science, or related technical field.
Preferred Qualifications
Reinforcement learning for LLMs: RLHF, GRPO, PPO, RLVR, reward modeling, RL scaling laws
Code generation and coding agents: repository-level code understanding, agentic coding
Agentic systems: multi-turn RL, tool-use planning, long-horizon task execution, user simulation
Distillation and alignment: on-policy distillation, reward-tilted distillation, cross-stage distillation to combine independently optimized capabilities into a single model
Long context and efficiency: sparse attention, context compression, scaling to very long context windows
Description
We are building the next generation of models optimized for Agentic, Reasoning, and Coding capabilities. This means training models via RL to reason from first principles, building autonomous coding agents that operate in real repositories, and developing agentic systems that handle multi-step workflows with error recovery. You will work on problems like: RL with verifiable rewards for mathematical reasoning, multi-turn RL for coding agents evaluated on SWE-Bench and beyond, scaling laws for RL compute allocation, progressive alignment across capability stages, and training models to manage their own context in long-horizon tasks. This is applied research with direct product impact - your work will ship to millions of users.
Minimum Qualifications
Demonstrated expertise in deep learning with publications at top ML or NLP conferences, or a track record of applying deep learning techniques to products
Proficient programming skills in Python and one of the deep learning toolkits such as JAX, PyTorch, or Tensorflow
Ability to work in a collaborative environment.
PhD, or equivalent practical experience, in Computer Science, or related technical field.
Preferred Qualifications
Reinforcement learning for LLMs: RLHF, GRPO, PPO, RLVR, reward modeling, RL scaling laws
Code generation and coding agents: repository-level code understanding, agentic coding
Agentic systems: multi-turn RL, tool-use planning, long-horizon task execution, user simulation
Distillation and alignment: on-policy distillation, reward-tilted distillation, cross-stage distillation to combine independently optimized capabilities into a single model
Long context and efficiency: sparse attention, context compression, scaling to very long context windows
About Apple
Sourced by ZipRecruiter
Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.
Industry
Computer and electronic product manufacturing
Company size
10,000+ Employees
Headquarters location
Cupertino, CA, US
Year founded
1976