Staff Machine Learning Engineer

Raft
London
6 months ago
Applications closed

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Staff Machine Learning Engineer

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Staff Machine Learning Engineer - Modeling

Staff Machine Learning Engineer

Staff ML Engineer

Location: Remote(GLOBAL) London PREFERABLE

Freight forwarding is a $200B+ industry you might not know about, but it’s the backbone of the global economy, ensuring goods move seamlessly around the world. Freight forwarders—like DHL, FedEx, and UPS—act as “travel agents” for goods, managing the complex operations that keep supply chains running.

Surprisingly, this critical industry remains largely untouched by modern software, with many processes still managed manually or through outdated systems. The eco-system is so fragile that one missed email can disrupt an entire shipment, leading to delays, poor service, and financial losses.

At Raft, we’re building an AI platform to automate freight operations. From auditing invoices and preparing customs filings to syncing information across systems, we empower operators to work more efficiently and accurately. The impact? Faster service, fewer errors, and more time for businesses to focus on growth and customer service.

We’re fortunate to have the support of top investors who are just as passionate as we do about transforming the industry, including Eight Roads (Alibaba, Spendesk, Toast), Bessemer Venture Partners (LinkedIn, Twilio, Shopify), Episode 1 (Zoopla, Betfair, Shazam), and Dynamo Ventures (Sennder, Stord, Gatik).

What You’ll Do:

  • 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.

Who You’ll Be:

  • 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.

 This role might not be for you if...

  • 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.



Apply Because You Want to...

  • 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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