Machine Learning Engineer
Apple · Bengaluru
- Experience5–10 yrs
- SalaryNot disclosed
- Work modeonsite
- Levelsenior
- Posted21 Sept 2026
About Apple
Apple is hiring in Bengaluru in semiconductors electronics. This role looks for around 5+ years of experience.
Skills
- machine learning
- AI systems
- predictive modeling
- statistical modeling
- supply chain forecasting
- optimization
- model inference services
- APIs
- data pipelines
- MLOps
- distributed computing
The role
A machine learning engineer at a semiconductor and electronics company designs predictive models and AI systems for supply chain forecasting and optimization, builds MLOps pipelines and model inference services, and develops Generative AI prototypes for structured reasoning and Text-to-SQL workflows.
Full job description
Job Summary
Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and theres no telling what you could accomplish. Are you an enthusiastic Machine Learning Engineer eager to apply your expertise in a fast-paced, innovative tech environment Join our Global Sourcing Supply Management (GSSM) Solutions team and help drive data-informed decisions across our supply chain.
As a Machine Learning Engineer on our core AI/ML team, you will analyze complex datasets, develop predictive and statistical models, and deliver insights that inform strategy and product direction. You will collaborate closely with business stakeholders, product teams, and data engineers to translate ambiguous questions into structured analyses and practical data-driven solutions. Your work will support experimentation, forecasting, optimization and measurable business impact across the supply chain.
Responsibilities
Design, develop, and deploy machine learning models and AI systems for forecasting, optimization, decision-making, and intelligent workflow automation
Build production-ready ML systems, including model inference services, APIs, data pipelines, and scalable ML applications
Develop and evaluate ML models using appropriate metrics, validation strategies, experimentation frameworks, and offline evaluation
Build analytical and AI-driven prototypes, including GenAI, LLM, structured reasoning, and Text-to-SQL workflows, and transition successful approaches into production
Design and implement scalable model inference services capable of supporting high-volume workloads with strong reliability and performance
Develop MLOps pipelines for model deployment, monitoring, evaluation, and continuous improvement
Monitor model performance, system reliability, latency, and resource utilization in production; identify and resolve performance issues
Partner with business and product teams to identify high-impact AI/ML opportunities and translate ambiguous requirements into scalable ML problem statements and measurable outcomes
Optimize models and ML systems for speed, scalability, efficiency, and cost
Collaborate closely with software engineering and data engineering teams on system design, distributed computing, APIs, and production architecture
Communicate technical trade-offs, system design decisions, model performance, and limitations clearly to technical and non-technical stakeholders
Stay current with emerging ML and GenAI techniques, prototype new approaches, and assess their applicability to supply chain challenges
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.