Jobs
Job Details:
Job Description:
We are looking for an AI / ML Engineer to join our AI group and help build, deploy, and operate reliable, production‑grade AI systems. This role is ideal for someone with ML knowledge AND a strong technical foundation who wants to grow within an enterprise environment, working on real‑world AI applications used at scale.
You will contribute to the full ML lifecycle, collaborating closely with data scientists, developers, and senior hardware engineers to transform research and prototypes into robust, maintainable, and well‑monitored production systems across cloud and on‑prem environments.
Key Responsibilities:
- Implementation, deployment, and maintenance of production‑grade ML models, AI agents, and end‑to‑end pipelines.
- Work with data scientists to help translate experimental models into scalable and reliable production solutions.
- Contribute to maintaining and improving ML systems with a focus on performance, scalability, and reliability.
- Follow and contribute to best practices for CI/CD, testing, documentation, and reproducibility.
- Participate in code reviews, design discussions, and post‑deployment reviews to continuously improve system quality.
What You’ll Gain:
- Hands‑on experience building production level AI systems.
- Mentorship from senior ML and AI engineers in a structured, supportive environment.
- Exposure to modern AI stacks, including LLMs, agentic workflows, and scalable ML infrastructure.
- Clear growth paths toward Senior AI / ML Engineer/Data Science roles.
Qualifications:
Qualifications:
- MSc in Computer Science, Statistics, Engineering or related field or BSc with at least 3 years of professional experience working with ML/AI systems.
- Strong Python/C# programming skills.
- Solid understanding of the ML lifecycle, from data preparation and training to deployment, evaluation, and monitoring.
- Experience in LLM pipelines and modern AI frameworks, OR hands‑on exposure through projects or coursework to tools such as Lang Graph, Lang Chain, or Llama Index.
- Foundational understanding of RAG concepts, prompt design, and production considerations (latency, cost, reliability).
Preferred Qualifications:
- Understanding of production AI use cases such as RAG systems, recommender systems, or LLM‑based services.
- Experience with cloud AI and agentic frameworks.
- Experience working in cross‑functional teams with product, engineering, and data stakeholders.
Job Type:
Experienced Hire
Shift:
Shift 1 (Israel)
Primary Location:
Israel, Haifa
Additional Locations:
Business group:
Silicon and Platform Engineering Group (SPE): Deliver breakthrough silicon and platform solutions that deliver industry-leading products today while also defining the next generation of computing experiences.
Posting Statement:
All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.
Position of Trust
N/A
Work Model for this Role
This role will require an on-site presence. Job posting details (such as work model, location or time type) are subject to change.
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About Intel

Intel
PublicIntel inside.
120,000+
Employees
Santa Clara
Headquarters
$200B
Valuation
Reviews
3.5
3 reviews
Work Life Balance
3.0
Compensation
3.0
Culture
2.5
Career
2.5
Management
2.0
25%
Recommend to a Friend
Pros
Offers internship opportunities
Interview opportunities available
Cons
Major job cuts and layoffs
Spam emails after rejection
Poor communication practices
Salary Ranges
6 data points
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
Mid/L4 · Data Scientist Grade 5
0 reports
$122,406
total / year
Base
-
Stock
-
Bonus
-
$104,045
$140,767
Interview Experience
2 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
Common Questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
System Design
Past Experience
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