Machine Learning Ops Engineer
Imagine what you could do here at Apple, new insights have a way of becoming excellent products, services, and customer experiences very quickly. What inspires you? Creating something new and finding solutions to sophisticated problems? Bring passion and dedication to your job and there’s no telling what you could accomplish. IS&T Corporate Systems team is looking for a creative and motivated Software Engineer with excellent problem solving and social skills. The work we do here has a large impact on Apple, from enabling our internal businesses to do their best work, to providing rich, highly usable experiences to our customers and partners. Our teams develop a collaborative environment with creative, expert & fun people using brand-new technologies. Engineering perfection is encouraged. Come join us for this once in a lifetime opportunity in building solutions for Apple that has worldwide impact.
As a Software Engineer you will be responsible in building the next generation of intelligent systems for Apple’s corporate applications. You will work in a dynamic environment to take an ideation to implementation in a multi-functional environment. The ideal candidate will be self-motivated, pro-active and solution oriented. Attention to detail and dedication to providing a high-quality, stable delivery are essential.
You will be challenged to find creative solutions to technical problems, feel comfortable working with sophisticated systems and large data sets, collaborating in a team environment. We promote innovation to improve our product performance and stay deeply focused on delighting our users.
- Bachelor’s degree in Computer Science or equivalent work experience.
- 3+ years of professional experience as a Software Engineer in AIML
- Prior experience or knowledge of working with machine learning & large language models
- Proficiency in programming languages such as Python, R, or Java.
- Knowledge of API development for serving generative models using Spring boot framework
- Experience with prompt engineering and vector embeddings.
- Knowledge of data engineering principles, including data preprocessing, ETL processes, and tools
- Proven track record of working on AI/ML projects from conception to deployment.
- Experience in maintaining data pipelines and working with streaming data processing frameworks like Apache Kafka, Flink, or Spark.
- Build end-to-end tooling for AI Development lifecycle within App Teams
- Pre-build components and reusable CI/CD templates
- Reduce time to AI-driven feature delivery
- Knowledge of LLM model architectures - GPT, BERT
- Experience interfacing with ML Platform team utilising and integrating ML APIs with applications
- Familiarity with ML libraries and frameworks, including TensorFlow, PyTorch, Pandas, and Scikit-learn.
- Understanding of RAG and graph-based RAG methodologies.
- Skills in rapid prototyping and experimentation with generative models