What you will be doing:
- Architect and optimize our existing data infrastructure to support cutting-edge machine learning and deep learning models.
- Collaborate closely with cross-functional teams to translate business objectives into robust engineering solutions.
- Own the end-to-end development and operation of high-performance, cost-effective inference systems for a diverse range of models, including state-of-the-art LLMs.
- Provide technical leadership and mentorship to foster a high-performing engineering team.
Requirements:
- Proven track record in designing and implementing cost-effective and scalable ML inference systems.
- Hands-on experience with leading deep learning frameworks such as TensorFlow, Keras, or Spark MLlib.
- Solid foundation in machine learning algorithms, natural language processing, and statistical modeling.
- Strong grasp of fundamental computer science concepts including algorithms, distributed systems, data structures, and database management.
- Ability to tackle complex challenges and devise effective solutions. Use critical thinking to approach problems from various angles and propose innovative solutions.
- Worked effectively in a remote setting, maintaining strong written and verbal communication skills. Collaborate with team members and stakeholders, ensuring clear understanding of technical requirements and project goals.
- Proven experience in Apache Hadoop ecosystem (Oozie, Pig, Hive, Map Reduce).
- Expertise in public cloud services, particularly in GCP and Vertex AI.
Must have:
- Proven expertise in applying model optimization techniques (distillation, quantization, hardware acceleration) to production environments.
- Proficiency and recent experience in Java is required (Must have)
- In-depth understanding of LLM architectures, parameter scaling, and deployment trade-offs.
- Technical degree: Bachelor's degree in Computer Science with a minimum of 10+ years of relevant industry experience, or
- A Master's degree in Computer Science with at least 8+ years of relevant industry experience.
- A specialization in Machine Learning is preferred.
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