Software Engineer

1 month ago

Montreal Quebec GF, CA Maxa AI Full time

About Maxa

For most companies, making sense of ERP and business data continues to require high levels of human skill and effort, repetitive spreadsheet and analytical work in addition to lengthy IT projects. Most business leaders agree this isn’t right, but don't have viable alternatives. This is especially true for finance, operations and supply chain executives and their teams.

Maxa automates turning raw data from multiple ERP and core systems into a single pre-computed stream of financial, operational, and supply chain insights ready to be consumed by executives and their teams.

About the role

We’re looking for motivated Software Engineers with proven experience in natural language processing (LLMs) to join our engineering team. You will collaborate closely with the C-Suite to further enhance the AI capabilities of Maxa’s flagship product, our self-serve BI platform.

Key Responsibilities

  • Work closely with cross-functional teams to align ML & LLM development with business challenges.
  • Develop & maintain production-grade code in Python and SQL.
  • Design, develop and deploy in production, machine learning models and algorithms as part of the general feature enhancements of the Maxa platform
  • Design, develop and deploy in production, LLMs as part of the Maxa platform’s business language understanding and generation capabilities
  • Fine-tune pre-trained LLMs to adapt to Maxa’s business context.
  • Collaborate with the data engineering team to preprocess data for LLM training and evaluation.
  • Define evaluation metrics and benchmarks to assess the performance of LLMs
  • Implement and maintain best practices in terms of MLOps/LLMOps for the Maxa platform
  • Work closely with DevOps and software engineering teams to integrate LLMs into the Maxa platform
  • Evaluate different LLM approaches (open source LLMs, agent architectures, prompting techniques etc.) to optimize the Maxa platform’s NLU performance.
  • Identify and resolve issues related to LLM performance, data quality, and integration.
  • Stay up-to-date with the latest on LLM techniques, share your knowledge and insights with the team and contribute to the growth of the organization's expertise in LLMs.

Strong Knowledge of:

  • Programming languages (Python and SQL) for production-grade deployment of ML models and LLMs
  • Popular databases such as Snowflake, PostgreSQL, MongoDB, etc.
  • Cloud platforms (e.g., AWS, Azure, GCP) and data warehouse platforms (e.g. Snowflake).
  • Container technology (Docker, Kubernetes)
  • Automated testing frameworks
  • Version control systems (e.g. Git)
  • Machine learning principles, algorithms and techniques.
  • LLM models, agent development tools and frameworks, such as OpenAI, open-source models (Mistral, LLAMA, etc.), Snowflake Cortex, Langchain etc.
  • Data manipulation, scientific computing and analysis tools (e.g., Pandas, NumPy/SciPy, Scikit-learn).
  • Deep learning frameworks like PyTorch
  • SnowPro Core Certification a plus

Be Familiar with:

  • NLP concepts and theory behind language models (LLMs), both traditional and modern (e.g. RNNs, Transformers etc.)
  • LLM fine-tuning, training, evaluation and prompting techniques
  • MLOps and LLMOps platforms
  • Vector databases (Faiss, Pinecone etc.)
  • Business & financial terminology

Soft Skills:

  • Excellent analytical and problem solving skills
  • Strong communication skills (verbal and written), with ability to interact with both technical and non-technical teammates.
  • Creative and innovative approaches to solving business challenges.
  • Obsessed with emerging technological trends (especially in machine learning & LLMs)

Qualifications

  • University degree (preferably Master’s or higher) in quantitative field (e.g., Computer Science, Statistics, Mathematics etc.) or related fields.
  • Proficient in English
  • 4+ years of experience as a ML Software Engineer, ML Engineer or similar role
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