Senior Machine Learning Engineer

Procurify is looking for an engaged and curious Senior Machine Learning Engineer who is passionate about technology and thrives on technological challenges. Everyone at Procurify is a team player. We’re seeking entrepreneurial people who are willing to challenge the status quo and contribute to larger strategic objectives.

Design, create, evolve, and maintain scalable and efficient machine learning systems including, data pipelines, model training, deployment, and monitoring frameworks.
KPIs: Model performance metrics (e.g. accuracy, precision, recall).

Build complex, reusable architectures for services and systems using well-accepted design patterns to support iterative development and future scaling.
KPIs: Architectural documentation completeness, scalability metrics.

Develop and enhance systems to deliver personalized experiences to our users, utilizing advanced machine learning and AI technologies to derive engagement and satisfaction.
KPIs: User engagement metrics, Satisfactions cores like NPS.

Create and optimize machine learning models to automate and streamline user workflows, enhancing operational efficiency and user experience.
KPIs: Model performance improvements, releasing automation features.

Integrate and leverage Large Language Models (LLMs) to develop advanced NLP features, including but not limited to chatbots, workflow automation agents and data analysis tools using state-of-the-art models (e.g. OpenAI, Anthropic, open source models).

5-7+ years in a Machine Learning role, including 1+ years experience in LLMs.

Proven experience as the first ML engineer or a similar role, demonstrating a strong ability to build ML systems from the ground up.

Proficiency in machine learning frameworks and libraries (e.g. Tensorflow, PyTorch, scikit-learn), as well as expertise in data processing and analysis (e.g., SQL, Pandas)

Experience in building with LLMs such as GPT, Claude, Llama etc and strong understanding of LLM architectures.

Experience with ETL/ELT tools, Data Lakehouse tech (Databricks, Python, Apache Spark, Hive, Parquet) and advanced SQL knowledge.

Strong programming skills in Python and familiarity with additional languages and tools commonly used in ML engineering.

Strong understanding of Data Science concepts, able to partner with and support team members who need to use data to predict trends, glean insights on business drivers, and answer questions that are relevant to the organization.

Comfortable leading by example and using influence to drive collaboration, documentation, and knowledge sharing across teams and with a broad range of stakeholders.

Able to demonstrate initiative, work independently, and thrive with autonomy while collaborating across teams in a culture of priority setting and moving forward with urgency in alignment with our organizational strategy

Adept at focusing on multiple competing priorities, solving unique and complex technical problems, and persistently resolving blockers to progress

Familiar with DevOps and MLOps principles such as design for manageability and root cause analysis

Familiar working within leading software development best practices such as scrum/kanban, CI/CD, and test automation