Staff Machine Learning Engineer

About project44

At project44, we believe in better. We challenge the status quo because we know a better supply chain isn't just possible—it's essential. Better for our customers. Better for their business. Better for the world.

With our Decision Intelligence Platform, Movement, we're redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.

Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India, we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose.

Since 2014, project44 has been transforming the way one of the largest, most important global industries does business. Our Advanced Visibility Platform is used by the world's leading brands to track shipments, collaborate with supply chain partners, drive operational efficiencies, and create outstanding customer experiences.

AI at project44

We expect every project44 team member, regardless of role or function, to actively leverage AI in their day-to-day work. Whether you're building product, serving customers, managing people, or running operations, AI is a tool you're expected to use with intent, curiosity, and judgment. We don't expect everyone to be a data scientist. We do expect everyone to be an intelligent user of AI: able to identify where it adds value, direct it effectively, evaluate outputs critically, and govern it responsibly. We invest in our team's AI fluency because we believe it's a competitive advantage for every person at project44, not just our engineers.

About the Role

Staff ML Engineer to lead the development of next-generation AI/ML systems at project44, spanning ETA, risk, anomaly detection, and supply chain intelligence. This role sits at the intersection of applied modeling, platform thinking, and production impact, with a mandate to both ship high-value ML capabilities and build reusable Data Science platform primitives that scale across teams.

In addition, this role will drive the integration of Generative AI, LLMs, and agentic systems into core workflows—enabling reasoning-driven diagnostics, automation, and intelligent decision support across the supply chain.

You will work closely with Data Science, ML Engineering, Data Engineering, Platform, and Product teams to deliver production-grade systems and establish a scalable, repeatable approach to AI development at P44.

What You'll Do

• Drive High-Impact ML Systems: Lead end-to-end development of models for ETA, risk, anomaly, and fraud—leveraging advanced techniques (embeddings, transformers, hybrid models).
• Build Data Science as a Platform: Develop reusable ML infrastructure (features, experimentation, deployment, monitoring) to scale model development and reduce time-to-production.
• Lead GenAI & Agentic Systems: Build LLM-powered solutions (RAG, diagnostics, automation, coding agents) and establish guardrails, evaluation, and explainability.
• Translate Business Problems into ML Solutions: Convert customer workflows into well-defined ML problems and ensure measurable business impact.
• Drive Experimentation & Evaluation: Establish strong offline/online evaluation frameworks tied to business outcomes.
• Collaborate Across Engineering: Partner with MLE and DE to build scalable, reliable systems across the ML lifecycle.

What We're Looking For

Experience

• 8–10+ years in Data Science / Applied ML with a strong track record of building and deploying production-grade ML systems.

Core Modeling & Technical Expertise

• Deep expertise across tree-based models, transformers, probabilistic modeling, and feature engineering, with a strong data-centric mindset.

Data & Platform Fluency

• Proficient in SQL and Python, with hands-on experience in modern data platforms (Snowflake/Databricks), pipelines (Spark, Airflow), streaming systems (Kafka), and MLOps tooling.

GenAI & LLM Capability

• Experience building RAG systems, working with embeddings and vector databases, and developing LLM-based applications and agentic workflows. Strong understanding of evaluation, guardrails, and safe deployment of GenAI systems.

Systems & Engineering Mindset

• Familiarity with distributed systems, APIs, and deployment patterns, with the ability to write clean, production-quality code.

Analytical Rigor & Diagnostics

• Strong ability to evaluate model performance, detect edge cases, run root cause analysis, and design robust monitoring and evaluation frameworks.

Data Quality & Signal Awareness

• Experience handling messy, real-world data, including drift, bias, missingness, and anomalies, along with tools and techniques to detect and address these issues.

Modeling Judgment & Trade-offs

• Ability to identify when to use ML versus heuristics and design pragmatic hybrid solutions. Strong understanding of architectural trade-offs across models and systems.

Business Impact Orientation

• Clear understanding of how ML metrics translate to business outcomes, with the ability to balance trade-offs across accuracy, scalability, latency, and customer experience.

Leadership & Communication

• Strong problem framing, stakeholder influence, and ability to communicate model behavior and decisions clearly to both technical and non-technical audiences. Proven track record of driving measurable business impact.

Preferred Skills

• Experience in logistics (Ocean, Truckload), supply chain, or high-volume operational systems
• Experience with geospatial data, routing, and tracking systems
• Experience with anomaly detection, fraud modeling, ETA prediction
• Experience building internal platforms or tools for DS teams

What Success Looks Like (6–12 Months)

• Deliver 2 high-impact ML capabilities with measurable customer value
• Establish standardized experimentation, monitoring, and RCA workflows
• Introduce GenAI/agentic capabilities that improve productivity and insight generation
• Reduce time-to-production and increase reuse across DS teams
• Drive measurable improvements in model performance and system reliability

Work Environment

This position requires a commitment to contribute to our collaborative culture by working in-office three days weekly.

Diversity & Inclusion

At project44, we're designing the future of how the world moves and is connected through trade and global supply chains. As we work to deliver a truly world-class product and experience, we are also intentionally building teams that reflect the unique communities we serve. We're focused on creating a company where all team members can bring their authentic selves to work every day.

We're building a company that every one of us at project44 is proud to work for, and our journey of becoming a more diverse, equitable and inclusive organization, where all have a sense of belonging, is shaped through the actions of our leadership, global teams, and individual team members. We are resolute in our belief that each team member has an equal responsibility to mold and uphold our culture.

project44 is an equal opportunity employer seeking to enrich our work environment by creating opportunities for individuals of all backgrounds and experiences to thrive. If you share our values and our passion for helping the way the world moves, we'd love to review your application!

For any accommodation needed during the hiring process, please email recruiting@project44.com. Even if you don't meet 100% of the above job description you should still seriously consider applying. Studies show that you can still be considered for a role if you meet just 50% of the role's requirements.