[Remote] Senior Engineering Manager at FourKites

Chennai, Tamil Nadu, India

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Supply Chain, Technology, LogisticsIndustries

Requirements

13+ years of software engineering experience, with 5+ years focused on ML/AI systems
5+ years of engineering management experience, including managing managers
Proven track record of shipping ML products at scale in production environments
Experience with full ML lifecycle: data collection, feature engineering, model training, deployment, and monitoring
Deep understanding of machine learning algorithms, deep learning, and statistical methods
Proficiency in ML frameworks (TensorFlow, PyTorch, JAX) and programming languages (Python, Scala, Java)
Experience with distributed computing frameworks (Spark, Ray) and cloud platforms (AWS, GCP, Azure)
Knowledge of MLOps tools and practices (Kubeflow, MLflow, Airflow, Docker, Kubernetes)
Understanding of data engineering, ETL pipelines, and big data technologies
Demonstrated ability to build and scale engineering teams
Strong communication skills with ability to influence at all levels of the organization
Experience driving technical strategy and making architectural decisions

Responsibilities

Define and execute the technical strategy for AI/ML initiatives across multiple product areas
Oversee the design and architecture of scalable ML systems, from data pipelines to model deployment
Drive decisions on technology stack, frameworks, and infrastructure for AI/ML workloads
Ensure engineering excellence through code reviews, design reviews, and technical mentorship
Stay current with AI/ML research and industry trends to inform strategic decisions
Lead, mentor, and grow a team of 15+ AI engineers, data scientists, and software engineers
Build high-performing teams through hiring, performance management, and career development
Foster a culture of innovation, collaboration, and continuous learning
Conduct regular 1:1s, performance reviews, and career development conversations
Champion diversity, equity, and inclusion initiatives within the engineering organization
Partner with Product Management to define AI product roadmap and priorities
Translate business objectives into technical initiatives and measurable outcomes
Manage multiple concurrent AI/ML projects from conception to production deployment
Establish and track KPIs for team performance, model quality, and system reliability
Balance innovation with pragmatic delivery to meet business deadlines
Work closely with Data Science, Product, Design, and other engineering teams
Communicate technical concepts and trade-offs to non-technical stakeholders
Represent engineering in executive discussions and strategic planning sessions
Build relationships with external partners, vendors, and research institutions
Drive alignment across teams on AI ethics, responsible AI practices, and governance
Establish best practices for ML model development, testing, and deployment
Implement MLOps practices for continuous integration and deployment of ML models
Ensure compliance with data privacy regulations and AI governance policies
Drive improvements in model monitoring, A/B testing, and experimentation frameworks
Manage engineering budget and resource allocation

Skills

Machine Learning

Data Pipelines

Model Deployment

Scalable Systems

Engineering Leadership

Technical Strategy

Code Reviews

Design Reviews

Hiring

Performance Management

Product Roadmap

FourKites

Real-time supply chain visibility platform

About FourKites

FourKites provides a platform for supply chain management that focuses on real-time visibility and predictive analytics. The platform collects data from millions of shipments worldwide and uses AI technology to analyze this data, offering businesses insights to improve their supply chain operations. This helps companies manage risks, enhance responsiveness, and optimize their processes. FourKites connects all parts of a supply chain through its applications, ensuring that teams have access to the same information. A unique feature of their platform is Fin AI, which uses natural language processing to help businesses find optimization opportunities and automate tasks. Unlike its competitors, FourKites stands out by combining a vast real-time supply chain network with specialized applications and patented AI technology. The goal of FourKites is to help large brands manage their supply chains more effectively and efficiently.

Chicago, IllinoisHeadquarters

2014Year Founded

$205.8MTotal Funding

LATE_VCCompany Stage

Data & Analytics, AI & Machine LearningIndustries

501-1,000Employees

Benefits

Medical, dental, & vision

PTO

401k with company match

Annual wellness stipend

Ongoing learning & development opportunities

Risks

Emergence of competitors like Auger with significant funding challenges FourKites' market share.

Overhaul's $55 million funding round intensifies competition in supply chain visibility.

Rapid market growth may attract more entrants, increasing competition for FourKites.

Differentiation

FourKites tracks 3 million shipments daily across multiple transportation modes.

The platform integrates real-time data with machine learning for end-to-end supply chain visibility.

FourKites' YardWorks suite optimizes gate and yard logistics with AI and computer vision.

Upsides

FourKites is recognized as a leader in Gartner's Magic Quadrant for four consecutive years.

The company collaborates with major brands like Organik Kimya and Clariant to enhance efficiency.

Growing demand for AI-powered supply chain tools boosts FourKites' market potential.

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