Senior Level AI/ML Researcher Jobs
Senior level ai/ml researcher jobs put experienced researchers in charge of setting technical direction, owning research outcomes, and leading the teams that move models from concept to production. Hiring concentrates across Technology & Software, Electronics & Hardware, and Banking & Financial Services, with 44% of openings remote or hybrid, and employers like Apple, General Motors, and UST hiring at this level now.
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Do you believe generative models can transform creative workflows and smart assistants used by billions? Do you believe it can fundamentally shift how people interact with devices and communicate, personalizing and tailoring experiences to their unique needs? SIML’s Content Understanding teams strives to turn cutting edge research into compelling user experiences that realize all these goals and more, working on Apple Intelligence technologies such as Image Playground, Genmoji, Generative Memories, Semantic Search, and many more.
You will be working alongside teams that are in charge of operating system wide embeddings, personalized RAG workstreams, tool calling, context compaction / efficiency & memory systems. Projects are focused on advancing Apple Intelligence capabilities, while working closely across disciplines with our partners in hardware engineering, design and product.
Description
We are looking for a senior technical leader experienced in architecting and deploying production scale multimodal ML. An ideal candidate has the ability to lead diverse cross functional efforts ranging from ML modeling, prototyping, validation and private learning. Solid ML fundamentals and an ability to place research contributions with respect to state of the art would be an essential part of the role. Experience with training and adapting large language models would be an important need.
This role includes the opportunity to partner with world class system engineers to prototype and incorporate bleeding edge algorithmic innovations in the context of emerging agentic experiences. Ability to interface with large scale modeling & data infrastructure is a huge plus.
Minimum Qualifications
PhD, or MSc in Computer Science/Electrical Engineering, or a related field (mathematics, physics or computer engineering); with a focus on machine learning, or comparable professional experience.
Hands on experience training LLMs/adapting pre-trained LLMs for downstream tasks & alignment.
Modeling experience at the intersection of NLP and Vision.
Proficiency in ML toolkit of choice, e.g., PyTorch.
Strong programming skills in Python.
Proven track record of research contributions demonstrated through publications in top-tier conferences, or open source contributions to algorithm.
Preferred Qualifications
Experience with building & deploying Multimodal-LLMs.
Familiarity with distributed training and large-scale data infrastructure.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $324,800, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Do you believe generative models can transform creative workflows and smart assistants used by billions? Do you believe it can fundamentally shift how people interact with devices and communicate, personalizing and tailoring experiences to their unique needs? SIML’s Content Understanding teams strives to turn cutting edge research into compelling user experiences that realize all these goals and more, working on Apple Intelligence technologies such as Image Playground, Genmoji, Generative Memories, Semantic Search, and many more.
You will be working alongside teams that are in charge of operating system wide embeddings, personalized RAG workstreams, tool calling, context compaction / efficiency & memory systems. Projects are focused on advancing Apple Intelligence capabilities, while working closely across disciplines with our partners in hardware engineering, design and product.
Description
We are looking for a senior technical leader experienced in architecting and deploying production scale multimodal ML. An ideal candidate has the ability to lead diverse cross functional efforts ranging from ML modeling, prototyping, validation and private learning. Solid ML fundamentals and an ability to place research contributions with respect to state of the art would be an essential part of the role. Experience with training and adapting large language models would be an important need.
This role includes the opportunity to partner with world class system engineers to prototype and incorporate bleeding edge algorithmic innovations in the context of emerging agentic experiences. Ability to interface with large scale modeling & data infrastructure is a huge plus.
Minimum Qualifications
PhD, or MSc in Computer Science/Electrical Engineering, or a related field (mathematics, physics or computer engineering); with a focus on machine learning, or comparable professional experience.
Hands on experience training LLMs/adapting pre-trained LLMs for downstream tasks & alignment.
Modeling experience at the intersection of NLP and Vision.
Proficiency in ML toolkit of choice, e.g., PyTorch.
Strong programming skills in Python.
Proven track record of research contributions demonstrated through publications in top-tier conferences, or open source contributions to algorithm.
Preferred Qualifications
Experience with building & deploying Multimodal-LLMs.
Familiarity with distributed training and large-scale data infrastructure.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $324,800, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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Senior Level AI/ML Researcher Jobs: Frequently Asked Questions
How do I get a senior level ai/ml researcher job?
Employers at this level look for candidates who have led published research, owned end-to-end model development, or driven measurable production impact rather than contributed to projects in a supporting role. A portfolio of first-author work, open-source contributions, or demonstrated influence on an organization's technical roadmap signals the ownership senior roles require. Mentoring experience and cross-functional collaboration also give candidates a clear edge.
Which companies hire senior level ai/ml researchers?
Companies hiring senior level ai/ml researchers right now include Apple, General Motors, and UST, based on current listings on Migrate Mate as of September 2026. Hiring at this level covers large technology firms running dedicated research labs, enterprise companies scaling AI capabilities, and well-funded startups building foundation-model products.
Are there remote senior level ai/ml researcher jobs?
Yes, remote and hybrid options are common at this level. About 44% of senior level ai/ml researcher openings are remote or hybrid as of September 2026, reflecting the research-oriented nature of the work and employer competition for experienced talent regardless of geography. On-site roles tend to cluster at labs where access to specialized hardware or collaborative research environments is central to the work.
What makes a ai/ml researcher role senior level?
A senior level ai/ml researcher role is defined by scope, ownership, and influence rather than task execution. These researchers independently define research agendas, make architectural decisions, and take accountability for outcomes. They mentor junior and mid-level team members, collaborate with engineering and product leadership, and contribute to the organization's long-term technical strategy, often shaping how an entire team approaches a problem area.
Which industries hire the most senior level ai/ml researchers?
Senior Level ai/ml researcher roles concentrate in Technology & Software, Electronics & Hardware, and Banking & Financial Services, based on current listings on Migrate Mate as of September 2026. These sectors drive hiring at this level because they are actively building proprietary models, scaling inference infrastructure, or applying advanced research to high-value domain problems that require deep technical leadership rather than applied engineering alone.