Lead R&D

Lead R&D AI/ML engineer is hands-on technical leaders who enjoy

• Designing and implementing data solutions best-suited to deliver on our customer needs and use cases — from streaming, to data lakes, to analytics, and beyond across a progressively evolving technical stack.
• Providing thought leadership by recommending the right technologies and solutions for a given use case, from the application layer to infrastructure; and have the team leadership and coding skills (e.g. Python, Java, and Scala) to get their solutions into production — and to help ensure performance, security, scalability, and robust data integration.
• Driving Customer success in a collaborative way while mentoring InData Labs data engineers.
• Switching between creating high level solutions and implementing those doing active development work.
• Enjoy working seamlessly across a variety of technical stacks

Required Experience:

• Proven experience as a technical team lead, and/or mentorship of other engineers
• Ability to develop end-to-end technical solutions
• Programming Expertise in Java, Python, Scala, or another modern programming language
• Strong working knowledge of SQL and the ability to write, debug, and optimize SQL queries
• Client-facing written and verbal communication skills and experience
• Create and deliver detailed presentations
• Detailed solution documentation (e.g. sequence diagrams, class hierarchies, logical system views, etc.)
• Establish scalable, efficient, and automated processes for large scale ML model deployments
• 4-year Bachelor’s degree in Computer Science or a related field

Prefer any of the following:

• Languages:
  • Python,  С++ (would be nice)
  • SQL, Gremlin (Cypher)
• Frameworks and libraries:
  • TensorFlow, TensorRT.
  • PyTorch.
  • Scikit-learn
  • NumPy
  • Pandas.
  • Jupyter Notebook.
  • PySpark, Dask, Polars
  • Flask/FastAPI
• Would be nice – understanding how to work with Edge/Mobile devices (limitations, AI libraries)
• Tools
  • Docker
  • Kubernetes
  • SageMaker
  • Google Colab
  • Git.
• Clouds:
  • AWS/GCP/Azure (Serverless architecture, AI/ML services, deployment)
• Databases, storages:
  • SQL (PostgreSQL/MySQL).
  • Non-SQL (MongoDB, Apache Kafka, Neo4j, AWS Neptune, Cassandra)
  • DWH (Snowflake, Redshift)
  • Apache Hadoop.
• Data Visualization:
  • Matplotlib.
  • Seaborn.
  • Plotly.
  • Tableau.
• Large Language Models (LLM):
  • Transformers ( GPT, BERT, RoBERTa etc.).
  • Hugging Face.
  • PyTorch-Transformers, TensorFlow-Transformers.
  • LLM Fine-tuning, Multi-GPU training
• Other:
  • MLFlow
• Would be nice:
  • Experience in Non-GPU (TPU/IPU) solutions
• Expertise/skills:
  • NLP (classical + DL)
  • Research, fast prototyping, documenting
  • MLOps
  • NN porting

Ideal opportunity if you enjoy

• Thinking independently and seeing the big picture
• Translating customer needs into solutions
• Confidently standing behind your recommendations
• Exploring new technologies in an effort to always grow and uncover better ways to solve problems (for instance: automating all the things)
• Explaining your technical decisions, both internally and externally
• Smiling in the face of complex problems
• Collaborating and helping your fellow data engineers learn and grow