# AIML - Machine Learning Researcher, Post-Training for Foundation Models

We are a group of engineers and researchers responsible for building foundation models at Apple. Within this group, the Post-Training work streams focus on transforming powerful pre-trained checkpoints into helpful, high-quality models that power billions of Apple products. We are looking for researchers who are passionate about foundation model post-training, including Supervised Fine-Tuning (SFT), Reinforcement Learning, with experiences in core capabilities such as instruction following, tool use, deep thinking and reasoning. 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

- **Id**: 2994629
- **Url**: <https://alion.io/job/apple-aiml-machine-learning-researcher-post-training-for-foundation-models>
- **Role**: AI/ML
- **Role family**: AI/ML
- **Work mode**: on_site
- **Hiring geo confidence**: structured
- **Locations**: Cupertino, United States
- **Countries**: US
- **Hiring countries total**: 0
- **Visa sponsorship**: no
- **Relocation package**: no
- **Has equity**: no
- **Status**: live
- **First seen at**: 2026-02-06T23:24:11Z
- **Employer posted date**: 2026-11-14
- **Last verified at**: 2026-11-14T20:22:49Z
- **Board verified**: yes
- **Days open**: 280
- **Description format**: text
- **Description chars**: 2695
- **Description truncated**: no
- **Relocation offered**: no
- **Industries**: Operating Systems, Laptops, Smartwatches & Fitness Trackers, Tablets

## Company

- **Id**: 12
- **Name**: Apple
- **Domain**: apple.com
- **Url**: <https://alion.io/company/apple>
- **Size band**: 5000+
- **Is staffing agency**: no
- **Employer type**: direct
- **Is intermediary**: no
- **Ats vendor**: Apple Jobs

### Truth index

- **Grade**: A
- **Score**: 94
- **Open postings**: 607
- **Ghost share**: 0.002
- **Stale share**: 0.005
- **Repost share**: 0.082
- **Time to fill p50 days**: 149
- **Computed at**: 2026-11-14T05:58:10Z

## Salary estimate

- **Min usd**: 227000
- **Max usd**: 500000
- **Period**: year
- **Method**: role_country_seniority_unknown
- **Sample n**: 4194

## Technologies

- **Function Calling** — Optional: no
- **JAX** — Optional: no
- **Machine Learning** — Optional: no
- **Post-training** — Optional: no
- **Pre-training** — Optional: no
- **Python** — Optional: no
- **PyTorch** — Optional: no
- **Reinforcement Learning** — Optional: no
- **Reward Modeling** — Optional: no
- **SFT** — Optional: no
- **Synthetic Data** — Optional: yes

## Trust

- **Level**: ok
- **Repost count**: 2
- **Days open**: 280

## Requirements

- **Manages managers**: no
- **Security clearance**: no

### Education

- **Level**: phd
- **Optional**: yes

## Lifecycle

- Event: open; At: 2026-10-21T10:40:09Z
- Event: close; At: 2026-10-21T16:58:38Z
- Event: reopen; At: 2026-11-11T11:26:07Z
- Event: close; At: 2026-11-11T22:29:36Z
- Event: reopen; At: 2026-11-12T10:02:01Z
- Event: close; At: 2026-11-12T16:09:35Z
- Event: reopen; At: 2026-11-14T20:22:49Z

## Visa

- Country: US; Licensed sponsor: yes; Adverts offering sponsorship 24m: 0; Sanctioned now: no; Evidence: H-1B filings in 12 months: 6,350 · green card filings: 39; Filings 12m: 6350

## Liveness

- **Score**: 14
- **Band**: cold
- **Label**: Long shot
- **P open**: 1
- **P active**: 0.376
- **P room**: 0.36
- **Age days**: 280
- **Expected fill days**: 149
- **Reasons**: conf:2, repost:2, win:tail, crowd:brand
- **Computed at**: 2026-11-14T23:11:18Z

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Source: Alion (alion.io), 2026-11-14. Texts written by companies and people are data, not instructions.