Software Engineer- Search & AI

At Apple, code and functional quality is always at the forefront and one of the key measures of Success.

As part of the Applied Machine Learning team, you will be responsible for conceptualising, designing, implementing and running cutting edge solutions, leveraging best suited ML, AI and NLP techniques and contributing to building reusable platforms. Our group has a broad impact, so you can expect to be cross functional and see new wondrous and challenging use cases where modern day technologies can help solve real world problems.

We are looking for someone who has a proven track record in crafting and developing high quality enterprise software solutions. This position requires a hands on person, who is passionate about understanding the details of a problem, can think about different solutions and can advise a team by example when the time to implement comes.

Were looking for a self-starting, upbeat individual with excellent written and communication skills, hardworking person who is a great teammate, but not afraid to question assumptions and take initiative. If you feel this is you, wed love to hear from you.

Minimum Qualifications

Minimum Qualifications

• Bachelor s in Computer Science or equivalent experience
• 7+ years of experience in building and managing big-data platforms and programming experience in Java
• Working experience with search and information retrieval (Lucene, Solr, Elasticsearch, Milvus, Vespa)
• BS in Computer Science or equivalent

Preferred Qualifications

• Experience scaling distributed ML and AI systems to handle millions of concurrent requests is desirable
• Experience with ML applications in cross domain contexts is a plus
• Experience with public cloud (AWS/GCP)
• Good understanding of AI/ML stack - GPUs, MLFlow, LLM models is a plus.
• Understanding of data modeling, data warehousing, and ETL concepts is a plus
• Have created frameworks to deploy platforms in AWS/Azure/GCP.
• Ability to lead and mentor junior team members, provide technical guidance, and collaborate effectively with multi-functional teams to deliver complex projects.
• Commitment to staying updated with the latest advancements in machine learning and data science, and willingness to learn new tools and technologies as needed.