Machine Learning Engineer

About Binoloop:

Binoloop is at the forefront of transforming decision-making through autonomous AI agents. Our flagship AI co-pilot, Tally, revolutionizes procurement evaluations—reducing evaluation times by 75% while ensuring transparency and compliance. We are now expanding our horizons with Atlas, a groundbreaking platform that empowers government contractors and engineers to build their own agentic workflows for procurement, sourcing, and contract management. At Binoloop, we strive to redefine AI's role in critical decision-making with responsible, cutting-edge innovations.

Role Overview:

We are seeking a highly experienced and innovative AI Engineer/Researcher to lead the design, development, and research of the Atlas platform. This role is for a passionate individual with a deep understanding of Machine Learning, Large Language Models (LLMs), and production-grade software development. You will drive the research, architecture, and implementation of a platform that enables customized autonomous agents for government and enterprise use cases. Additional emphasis will be placed on developing Retrieval Augmented Generation (RAG) systems for optimal data retrieval, integrating advanced reasoning techniques, and fine-tuning LLMs for high-stakes environments. Preference will be given to candidates based in Alberta.

Key Responsibilities:

• Platform & Workflow Development:
• Lead the research, design, and development of Atlas, focusing on customizable agentic workflows for procurement, sourcing, and contract management.
• Architect and implement advanced LLM-based systems that integrate seamlessly with government legacy systems and manual workflows.
• Advanced AI & Data Retrieval:
• Design, build, and optimize RAG systems to efficiently retrieve and integrate data from diverse sources.
• Develop innovative methodologies for reasoning, decision-making, and interpretability in LLMs for high-stakes environments.
• Fine-tune and optimize LLMs using the latest reasoning techniques to enhance performance and reliability.
• Agentic Frameworks & Software Integration:
• Integrate agentic frameworks such as Langgraph, LangChain, and CrewAI into the platform to enable intelligent, autonomous agents.
• Leverage additional libraries and tools (e.g., Hugging Face Transformers, PyTorch, TensorFlow) to build, test, and deploy robust AI models.
• Production-Grade Engineering:
• Build scalable and production-ready ML pipelines and APIs using Python and FastAPI.
• Adhere to industry-standard coding practices including rigorous logging, unit testing (e.g., using pytest), version control, and CI/CD processes.
• Collaborate closely with MLOps teams to streamline deployment, model inference optimization, and lifecycle management.
• Research & Collaboration:
• Stay current with advancements in AI, ML, and NLP, incorporating innovative features into the Atlas platform.
• Mentor team members and foster a collaborative, research-driven environment by contributing to whitepapers, publications, or internal documentation.
• Ensure that all developments adhere to AI ethics, compliance, and unbiased decision-making principles.

Qualifications:

• Education & Experience:
• Degree in Engineering, Computer Science, Machine Learning, Artificial Intelligence, or a related field (or equivalent professional experience).
• 3+ years of experience in building and deploying machine learning or NLP models in production environments.
• Technical Expertise:
• Proven experience with Large Language Models (LLMs), including model fine-tuning and optimization.
• Demonstrated ability in building and optimizing RAG systems for effective data retrieval.
• Strong proficiency in Python and production-grade API development using FastAPI.
• Expertise with agentic frameworks such as Langgraph, LangChain, and CrewAI.
• Familiarity with ML libraries and tools such as Hugging Face Transformers, PyTorch, TensorFlow, etc.
• Hands-on experience in building scalable ML pipelines, integrating knowledge graphs, and semantic search capabilities.
• Understanding of MLOps practices including containerization (e.g., Docker) and CI/CD pipelines.
• Solid grasp of model inference processes and optimization techniques.
• Research & Innovation:
• Prior research experience (evidenced by publications or active involvement in AI research) is highly valued.

Soft Skills:

• Exceptional analytical and critical thinking abilities.
• Strong written and verbal communication skills, with the capability to explain complex technical concepts clearly.
• A collaborative mindset with proven success in multidisciplinary team environments.
• Proactive, self-driven, and passionate about AI research and development in a fast-paced startup culture.

Why Join Binoloop?

• Play a pivotal role in developing Atlas—a platform that redefines government workflows through AI-driven innovation.
• Work on cutting-edge AI technologies that have a real-world impact on government and enterprise sectors.
• Collaborate with top-tier researchers and engineers in a dynamic, mission-driven startup environment.
• Enjoy competitive compensation, flexible work arrangements, and ample opportunities for professional growth.

Join Binoloop and help transform the way government and enterprise organizations harness the power of AI.