Staff AI/ML Engineer
- Lead the design and deployment of end-to-end ML systems for enterprise applications, from experimentation to production.
- Apply large language models effectively:
- Fine-tune and evaluate LLMs for domain-specific tasks.
- Develop robust prompt engineering and orchestration strategies.
- Optimize inference pipelines for latency, throughput, and cost-efficiency.
- Write production-quality software with strong engineering rigor-designing clean APIs, building reliable systems, and collaborating closely with product engineers.
- Build high-reliability ML infrastructure: training pipelines, model registries, observability, and CI/CD for ML.
- Ensure ML solutions meet enterprise standards for security, compliance, data privacy (e.g., SOC2, GDPR), explainability, and auditability.
- Develop evaluation and monitoring frameworks that measure accuracy, fairness, robustness, and drift in deployed models.
- Partner with product and GTM teams to identify high-value enterprise use cases for ML and translate them into scalable solutions.
- Work directly with customer facing teams to help with important enterprise customer projects.
- Mentor engineers and raise the bar for technical excellence across the org.
- Influence technical strategy and help define the company's long-term AI roadmap.
- An experienced Python developer with a strong grasp of data structures and algorithms, and an understanding of CI/CD pipelines.
- A Machine Learning professional proficient in data wrangling (SQL, pandas, NumPy) and scripting. You'll be skilled in supervised and unsupervised learning, model evaluation, and feature engineering.
- Knowledgeable in Deep Learning frameworks like PyTorch, with experience in various neural networks and NLP models. Exposure to generative and multi-modal models is a plus.
- A practitioner of MLOps, experienced in model serving, orchestration (Kubernetes), and experiment tracking. You'll be capable of designing and delivering large-scale ML systems and platforms, with a focus on cost optimization and reproducibility.
- Equipped with a solid foundation in linear algebra, probability, statistics, and calculus.
- An effective communicator who can translate complex technical concepts into clear business language and work collaboratively with non-technical stakeholders. You'll also be expected to provide technical leadership and mentor colleagues.
- You're only interested in research or purely theoretical ML problems without building and maintaining production systems.
- You prefer working on consumer-facing applications over complex B2B SaaS platforms.
- You're not interested in providing technical leadership or mentoring a team through code reviews and architectural guidance.
- You're not comfortable taking ownership of projects end-to-end, from data ingestion to final delivery.
- Join a dynamic, fast-growing company at the forefront of logistics technology, where you'll be interacting with clients across various industries.
- Work in a client-centric role where your technical expertise helps solve real-world challenges for global businesses.
- Collaborate with diverse teams to create customized solutions that have a tangible impact on the efficiency of the logistics and freight industry.
- Thrive in a customer-facing, dynamic environment where you can grow your technical and communication skills.
- Be part of a diverse, inclusive, and multi-cultural team that values continuous learning and innovation.
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