Lead Data Scientist

1 month ago

Bengaluru, India Zyoin group Full time

Responsibilities :

- Develop and deploy scalable deep learning models to improve the search experience of Target guests.

- Architect and implement large-scale AI systems using test-driven development practices.

- Build NLP technology for query and document analysis, processing, and understanding.

- Create data pipelines for feature/label extraction and generation.

- Conduct data analysis to identify opportunities and improve models.

- Research to advance state-of-the-art machine learning and NLP technologies.

- Contributing to the operations/building of AI pipelines.

- Adopting Target's infrastructural platforms and operationalizing tools and systems around them.

- Mentor and partner with other engineers to develop software that meets business needs.

- Follow agile methodology for software development and technical documentation.

- Innovate constantly and keep systems up to date with current technologies.

Requirements :

- MS or Ph.D. degree in Computer Science, Electrical Engineering, Mathematics, or a related field.

- Research or industrial experiences in relevant fields, such as information retrieval, machine learning, NLP, or recommendation systems.

- 8+ years of experience in deploying machine learning algorithms into production environments.

- Proficient in Python or Java with Strong coding and problem-solving skills.

- Solid modeling skills in Python.

- Good understanding of search indexing, retrieval, and ranking.

- Extensive experience in implementing and integrating ML models in production with high traffic.

- Experience querying large databases with SQL, HQL, or some variations.

- Experience with Semantic Search is a plus.

- Experience in Tuning LLMs is a plus.

- Proven track record of achieving significant engineering or academic results.

- Excellent interpersonal and communication skills to work with global teams

Bonus Points :

- Proven track record of achieving significant engineering (applied ML) or academic research.

- Experience with vector DBs and LLMs, RAG.

(ref:hirist.tech)

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