Join us at Enquo, where we're dedicated to harnessing the transformative power of data and technology. As leaders in technology and data solutions, we prioritize humanity in everything we do. Our mission is clear: to empower organizations to unlock the full potential of their data through cutting-edge technology and exceptional services.

We envision a brighter future, where technology ignites extraordinary achievements and drives profound transformation. Here at Enquo, challenges are opportunities, and our passionate team thrives on making meaningful impacts on society. With humility and a collaborative spirit, we leverage teamwork and creative thinking to deliver optimal and trustworthy solutions.

Asa purpose-driven company, were passionate about using data and technology as catalysts for positive change. Our vision extends to a world where everyone can harness the power of data to reach their fullest potential. At Enquo, honesty, trust, and empathy form the foundation of our simple business language. Were agile, adaptable, and committed to bridging any business need with innovative data solutions.

Join our journey, where curiosity and entrepreneurship drive us to explore uncharted territories and create solutions that truly matter. We foster a collaborative and inclusive environment, valuing every team member's contributions. If you're a talented, curious, and creative individual who thrives in a fast-paced, dynamic setting, we invite you to be part of our mission. Together, let's create new opportunities through data and technology, shaping a more humane future for all.

Enquo: fueling a better future through innovation, data, and technology.

We are seeking a Head of Engineering with balanced expertise in Machine Learning (ML)/ML Operations (MLOps) and core software engineering to spearhead our engineering initiatives for an innovative web application product. This role demands a leader who not only has a profound technical grounding in both ML/MLOps and software development but also possesses the strategic acumen to merge these disciplines seamlessly. We aim to find a leader who can drive our engineering team towards excellence in both machine learning innovation and robust software engineering practices.

• Develop and execute a cohesive strategy that equally emphasizes advancements in ML/MLOps and core software engineering practices, ensuring they collectively support and enhance our product's vision and capabilities
• Oversee the development, scaling, and optimization of our ML platform while ensuring the software engineering foundations are solid, scalable, and maintainable. This includes leading efforts in system architecture, API design, data processing, and infrastructure that supports both machine learning and application development
• Guide the team in adopting and innovating in the areas of machine learning model development, deployment, monitoring, and management. Ensure the ML lifecycle is fully integrated with our CI/CD pipelines, Kubernetes, emphasizing automation, reproducibility, and scalability
• Champion best practices in software development, including design patterns, code quality, security, and performance. Ensure that our core software engineering practices enable and enhance our ML capabilities, fostering a culture of excellence
• Lead, mentor, and lead a diverse distributed engineering team of software developers, ML engineers, and data engineers. Create an environment that encourages innovation, collaboration, and continuous learning across both software engineering and ML/ML Ops domains
• Serve as a bridge between the ML/MLOps and software engineering teams, ensuring tight integration and collaboration. Work closely with product management, UX/UI designers, and other stakeholders to deliver a seamless, high-quality product

• At least 10 years of technology experience, with experience in leadership roles managing teams that specialize in both ML/MLOps and core software engineering. Experience with ML metrics observability, workflow orchestration, service release automation, notebook development, and LLM deployment is a plus
• A deep understanding of Enterprise Software architecture, design patterns, and modern programming languages coupled with a strong foundation in machine learning algorithms, data modeling, and MLOps practices across the major cloud providers (AWS, Azure, GCP)
• Proven ability to lead, inspire, and grow multidisciplinary engineering teams. A Strategic thinker with the capacity to balance short-term goals with long-term vision
• Excellent communication and collaboration skills, capable of fostering positive relationships across engineering teams and with other business units • Advanced degree in Computer Science, Engineering, or a related field, with a strong background in both AI/machine learning and software engineering