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Senior Machine Learning Engineer
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Senior Machine Learning Engineer
2 months ago
We are seeking a seasoned Senior Machine Learning Engineer to design, build, and optimize a cutting-edge Machine Learning inference platform. The ideal candidate will have significant expertise in Machine Learning engineering and infrastructure, with a focus on building scalable and efficient Machine Learning inference systems.
Key Responsibilities:- Architect and optimize our existing data infrastructure to support advanced 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 Large Language Models.
- Provide technical leadership and mentorship to foster a high-performing engineering team.
- Proven track record in designing and implementing scalable and cost-effective Machine Learning 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.
- Expert-level proficiency in at least one programming language such as Java, Python, or C++.
- Ability to tackle complex challenges and devise effective solutions using critical thinking and innovative problem-solving skills.
- Experience working effectively in a remote setting, maintaining strong written and verbal communication skills, and collaborating with team members and stakeholders.
- Proven experience in Apache Hadoop ecosystem (Oozie, Pig, Hive, Map Reduce).
- Expertise in public cloud services, particularly in GCP and Vertex AI.
- Proven expertise in applying model optimization techniques (distillation, quantization, hardware acceleration) to production environments.
- In-depth understanding of LLM architectures, parameter scaling, and deployment trade-offs.
- Technical degree: Bachelor's degree in Computer Science with a minimum of 8 years of relevant industry experience, or a Master's degree in Computer Science with at least 6 years of relevant industry experience. A specialization in Machine Learning is preferred.
