Responsibilities

• GPU Infrastructure Management: Design, set up, and maintain robust local GPU-based infrastructure operations.
• Pipeline Development: Develop and manage end-to-end pipelines for building, training, evaluating, and deploying LLMs.
• Inference Management: Implement and manage inference workloads, ensuring scalability and reliability in production environments.
• Collaborative Development: Work closely with data scientists and software engineers to integrate machine learning models into production systems, ensuring seamless operation and high performance.
• Benchmarking and Optimization: Develop benchmarks to evaluate model performance and optimize algorithms for efficiency and accuracy in legal-specific tasks.
• Research and Prototyping: Rapidly prototype new ideas and solutions, staying at the forefront of emerging technologies and methodologies.
• Continuous Learning: Engage in continuous learning and demonstrate relevant projects through GitHub or similar platforms, showcasing your ability to learn and deliver innovative solutions.

Qualifications

• Technical Proficiency:
  • Experience with GPU-based infrastructure and parallel computing.
  • Very proficient in Python and core LLM libraries (e.g. PyTorch, Transformers, vLLM, WeightsAndBiases).
  • Strong background in building and deploying machine learning models.
  • Experience with ML infrastructure management, either via cloud providers or local infrastructure.
  • Solid understanding of data pipelines, ETL processes, and model lifecycle management.
• Collaboration and Communication:
  • Excellent verbal and written communication skills.
  • Ability to work effectively in a multidisciplinary team environment, bridging the gap between data science and engineering.
• Problem-Solving and Innovation:
  • Strong problem-solving skills with a creative and innovative mindset.
  • Ability to prototype and experiment with new technologies and approaches.
• Learning and Adaptability:
  • Demonstrated ability to quickly learn new technologies and adapt to changing requirements.

Nice-to-Have:

• Experience with air-gapped environments: Familiarity with working with highly sensitive data in high-security environments.
• Multi-modal Experience: Familiarity with multi-modal data and multi-model models.
• Graph databases: Familiarity with native graph databases (e.g. Neo4J) and integration with AI products.
• Custom GPU kernel development: Experience with developing custom GPU kernels for high-performance accelerated computing.

Why Join Us?

• Innovative Environment: Work at the cutting edge of AI and legal tech, where your contributions will directly impact the development of advanced solutions for the legal industry.
• Local GPUs: Manage a growing cluster of state-of-the-art GPU machines and work with our data science team to push them to the limits of performance.
• Collaborative Culture: Join a team of passionate engineers with a start-up mindset, dedicated to pushing the boundaries of technology.
• Career Growth: Opportunities for professional development and career advancement in a cutting-edge field.

Hiring process

Please note that our hiring process requires you to complete a technical assessment that should take no longer than 60 minutes.

We also require you to submit at least one publicly accessible project for review (e.g. on github).

Consilio’s True North Values

• Excellence
  We strive to make every client our advocate
• Passion
  We DO because we CARE
• Collaboration
  We win together through teamwork and communication
• Agility
  We flex, adapt and embrace change
• People
  We value, respect and invest in our teammates
• Vision
  We create clarity of purpose and a clear path forward