FourKites

<html><body><div class="job__description body">  <div><p><em><span>At FourKites we have the opportunity to tackle complex challenges with real-world impacts. Whether it’s medical supplies from Cardinal Health or groceries for Walmart, the FourKites platform helps customers operate global supply chains that are efficient, agile and sustainable.</span></em></p><p><em><span>Join a team of curious problem solvers that celebrates differences, leads with empathy and values inclusivity</span></em><strong><em>. </em></strong></p><p>We are seeking an experienced Senior Engineering Manager to lead our AI/ML engineering teams in building cutting-edge artificial intelligence solutions. This role requires a unique blend of technical expertise in AI/ML, proven engineering leadership, and strategic thinking to drive innovation at scale.</p><h2><strong>Key Responsibilities</strong></h2><h3><strong>Technical Leadership</strong></h3><ul><li>Define and execute the technical strategy for AI/ML initiatives across multiple product areas</li><li>Oversee the design and architecture of scalable ML systems, from data pipelines to model deployment</li><li>Drive decisions on technology stack, frameworks, and infrastructure for AI/ML workloads</li><li>Ensure engineering excellence through code reviews, design reviews, and technical mentorship</li><li>Stay current with AI/ML research and industry trends to inform strategic decisions</li></ul><h3><strong>People Management</strong></h3><ul><li>Lead, mentor, and grow a team of 15+ AI engineers, data scientists, and software engineers</li><li>Build high-performing teams through hiring, performance management, and career development</li><li>Foster a culture of innovation, collaboration, and continuous learning</li><li>Conduct regular 1:1s, performance reviews, and career development conversations</li><li>Champion diversity, equity, and inclusion initiatives within the engineering organization</li></ul><h3><strong>Strategic Planning & Execution</strong></h3><ul><li>Partner with Product Management to define AI product roadmap and priorities</li><li>Translate business objectives into technical initiatives and measurable outcomes</li><li>Manage multiple concurrent AI/ML projects from conception to production deployment</li><li>Establish and track KPIs for team performance, model quality, and system reliability</li><li>Balance innovation with pragmatic delivery to meet business deadlines</li></ul><h3><strong>Cross-functional Collaboration</strong></h3><ul><li>Work closely with Data Science, Product, Design, and other engineering teams</li><li>Communicate technical concepts and trade-offs to non-technical stakeholders</li><li>Represent engineering in executive discussions and strategic planning sessions</li><li>Build relationships with external partners, vendors, and research institutions</li><li>Drive alignment across teams on AI ethics, responsible AI practices, and governance</li></ul><h3><strong>Operational Excellence</strong></h3><ul><li>Establish best practices for ML model development, testing, and deployment</li><li>Implement MLOps practices for continuous integration and deployment of ML models</li><li>Ensure compliance with data privacy regulations and AI governance policies</li><li>Drive improvements in model monitoring, A/B testing, and experimentation frameworks</li><li>Manage engineering budget and resource allocation</li></ul><h2><strong>Required Qualifications</strong></h2><h3><strong>Experience</strong></h3><ul><li>13+ years of software engineering experience, with 5+ years focused on ML/AI systems</li><li>5+ years of engineering management experience, including managing managers</li><li>Proven track record of shipping ML products at scale in production environments</li><li>Experience with full ML lifecycle: data collection, feature engineering, model training, deployment, and monitoring</li></ul><h3><strong>Technical Skills</strong></h3><ul><li>Deep understanding of machine learning algorithms, deep learning, and statistical methods</li><li>Proficiency in ML frameworks (TensorFlow, PyTorch, JAX) and programming languages (Python, Scala, Java)</li><li>Experience with distributed computing frameworks (Spark, Ray) and cloud platforms (AWS, GCP, Azure)</li><li>Knowledge of MLOps tools and practices (Kubeflow, MLflow, Airflow, Docker, Kubernetes)</li><li>Understanding of data engineering, ETL pipelines, and big data technologies</li></ul><h3><strong>Leadership Competencies</strong></h3><ul><li>Demonstrated ability to build and scale engineering teams</li><li>Strong communication skills with ability to influence at all levels of the organization</li><li>Experience driving technical strategy and making architectural decisions</li><li>Track record of successful cross-functional collaboration and stakeholder management</li><li>Ability to balance technical depth with business acumen</li></ul><h2><strong>Preferred Qualifications</strong></h2><ul><li>Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field</li><li>Deep experience with Large Language Models (LLMs), Small Language Models (SLMs), and generative AI applications</li><li>Expertise in building production AI agent systems:</li><ul><li>Multi-agent architectures and swarm intelligence</li><li>Memory systems: short-term, long-term, episodic, and semantic memory</li><li>Planning algorithms: hierarchical planning, goal decomposition, and backtracking</li><li>Tool use and function calling optimization</li><li>Agent communication protocols and coordination strategies</li></ul><li>Experience with advanced agent frameworks: DSPy, Guidance, LMQL, Outlines for constrained generation</li><li>Knowledge of prompt engineering techniques: few-shot, chain-of-thought, self-consistency, constitutional AI</li><li>Experience with RAG architectures: vector stores, hybrid search, re-ranking, and query optimization</li><li>Expertise in training techniques: supervised fine-tuning, RLHF, DPO, PPO, constitutional AI, and synthetic data generation</li><li>Experience with parameter-efficient fine-tuning methods: LoRA, QLoRA, prefix tuning, and adapter layers</li><li>Knowledge of model optimization techniques: quantization (INT8, INT4), distillation, pruning, and flash attention</li><li>Extensive experience in dataset curation for LLM training:</li><ul><li>Web-scale data processing (Common Crawl, C4, RefinedWeb methodologies)</li><li>Creating instruction-tuning datasets (Alpaca, Dolly, FLAN-style formats)</li><li>Building preference datasets for RLHF/DPO training</li><li>Domain adaptation and specialized corpus creation</li><li>Multi-lingual and code dataset preparation</li></ul><li>Knowledge of data mixing strategies, replay buffers, and curriculum learning for optimal training</li><li>Experience with data augmentation techniques: paraphrasing, back-translation, and synthetic data generation using LLMs</li><li>Expertise in data decontamination and benchmark pollution prevention</li><li>Experience with workflow automation platforms: n8n, Zapier, Make for business process automation</li><li>Knowledge of enterprise integration patterns: event-driven architectures, saga patterns, and CQRS</li><li>Strong background in data science: statistical analysis, A/B testing, experimentation design, and causal inference</li><li>Experience with data mesh architectures and building self-serve data platforms</li><li>Expertise in data quality frameworks, data contracts, and SLA management for data pipelines</li><li>Experience with vector databases (Pinecone, Weaviate, Qdrant, Milvus, ChromaDB, FAISS) and embedding systems</li><li>Knowledge of privacy-preserving ML techniques: differential privacy, federated learning, secure multi-party computation</li><li>Background in specific AI domains: NLP, Computer Vision, Recommendation Systems, or Reinforcement Learning</li><li>Experience with LLM evaluation frameworks and benchmarking (HELM, EleutherAI eval harness, BigBench)</li><li>Hands-on experience with popular LLM frameworks: Hugging Face Transformers, vLLM, TGI, Ollama, LiteLLM</li><li>Experience with dataset processing tools: Datasets library, Apache Beam, Spark NLP</li><li>Publications or contributions to open-source ML projects</li><li>Experience in high-growth technology companies or AI-first organizations</li><li>Knowledge of AI safety, ethics, and responsible AI practices</li><li>Experience with multi-modal models and vision-language models</li></ul><h2><strong>What We Offer</strong></h2><ul><li>Opportunity to work on cutting-edge AI technology with real-world impact</li><li>Competitive compensation package including equity</li><li>Access to state-of-the-art computing resources and research tools</li><li>Budget for conferences, training, and professional development</li><li>Collaborative environment with talented engineers and researchers</li><li>Flexible work arrangements and comprehensive benefits</li></ul><p><strong>Who we are:<br/><br/></strong>FourKites®, the leader in AI-driven supply chain transformation for global enterprises and pioneer of advanced real-time visibility, turns supply chain data into automated action. FourKites’ Intelligent Control Tower™ breaks down enterprise silos by creating a real-time digital twin of orders, shipments, inventory and assets. This comprehensive view, combined with AI-powered digital workers, enables companies to prevent disruptions, automate routine tasks, and optimize performance across their supply chain. FourKites processes over 3.2 million supply chain events daily — from purchase orders to final delivery — helping 1,600+ global brands prevent disruptions, make faster decisions and move from reactive tracking to proactive supply chain orchestration.<br/><strong><br/>Working at FourKites<br/></strong><br/>We provide competitive compensation with stock options, outstanding benefits and a collaborative culture for all employees around the globe, including:</p><div><ul><li>5 global recharge days, in addition to standard holidays, and a hybrid, flexible approach to work.</li><li>Parental leave for all parents, an annual wellness stipend and volunteer days also provide you with time and resources for self care and to care for others.</li><li>Opportunities throughout the year to learn and celebrate diversity.</li><li>Access to leading AI tools and foundation models, with the freedom to experiment and find creative ways to be more effective in your role</li></ul>And we're always listening for new ways to support everyone in and out of the office.</div></div></div></body></html>

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