Director of Machine Learning

About Us:

Onclusive is the global benchmark for integrated media content, turning enriched data into actionable insight across every channel - online, print, broadcast and social. Our scalable solutions meet real-world needs: from direct integration of enriched data into your ecosystem, self-service tools that track, measure, and manage media impact, to expert analysis that guides sharper decisions. Powered by innovation and elevated by people, we help you protect brand reputation, prove impact, and continually improve your value.  

 

About the role:

We are looking for a Director of AI & ML Engineering to lead Onclusive's AI and machine learning function across our platform. This is a hands-on leadership role for someone with deep technical expertise and a strong track record of building, scaling, and delivering production AI/ML systems that create measurable business value. As a player-coach, this key role will drive customer value with rapid innovative product improvements across Onclusive’s product suite using AI capabilities. 

You will define the AI/ML strategy, drive execution across a cross-functional organisation, and develop a high-performing team, while maintaining technical credibility across the organisation. You will partner with product, engineering, data platform and business stakeholders to translate real-world media analytics problems into scalable, production-grade systems spanning NLP, computer vision, semantic search, information retrieval and agentic AI.

This is a full-time on-site role based in India. Preferred location is Bangalore or Mumbai. 

 

Your responsibilities:

Strategic Leadership:

• Define and own the long-term AI/ML strategy aligned with Onclusive's product roadmap and business objectives, spanning NLP, entity recognition, sentiment, semantic search, and generative AI

• Identify high-impact use cases across our products suite and collaborate with product and engineering teams to deliver them

• Serve as a thought leader for AI/ML within the organisation, advocating for modern approaches, emerging technologies, and engineering best practices

• Translate business problems into well-scoped AI products with clear success metrics - accuracy, latency, cost, and measurable product impact

 

Technical and Delivery Leadership:

• Provide technical leadership across the full ML lifecycle - research, design, experimentation, validation, deployment, and continuous improvement - setting the direction and raising the bar for the team

• Establish and evolve robust MLOps practices ensuring reproducibility, reliability, observability, cost effectiveness, and consistent high-quality model delivery

• Define architectural standards for production ML systems including data pipelines, embedding infrastructure, self-hosted models and agentic AI capabilities

• Champion software engineering best practices across the team - code standards, code review, version control, CI/CD, testing, and documentation

• Drive Agile delivery practices including sprint planning, quarterly OKRs, technical reviews, and retrospectives to maintain a healthy execution cadence

• Oversee the design and delivery of data pipelines supporting AI features, including batch processing, event-driven architectures, and feedback loops

• Review system designs and provide technical guidance on critical architectural decisions, unblocking the team where needed

 

People and Team Leadership:

• Coach-player approach with people management responsibilities for key people

• Mentor and develop a cross-functional team of ML engineers, data scientists, and platform engineers spanning traditional ML, generative AI, and MLOps

• Scale and develop a high-performing AI/ML organisation, maintaining high retention and a strong engineering culture

• Set clear expectations, provide regular feedback, and support the professional growth and progression of team members

• Drive a rigorous interview and hiring process, maintaining a high technical bar for all hires

 

Cross-Functional Collaboration:

• Partner closely with product management to define AI/ML roadmaps, prioritise initiatives, and ensure timely, high-impact delivery

• Collaborate with data platform, security, and compliance teams to ensure ML systems are scalable, secure, and compliant with GDPR, EU AI Act, and SOC2 requirements

• Communicate clearly and accurately to leadership and the broader organisation, operating with full transparency

• Represent the AI/ML function in cross-company forums related to AI strategy, governance, and innovation

 

Who you are:

• Graduate studies in Computer Science, Applied Mathematics, Statistics, or a related technical field - or equivalent depth of industry experience; an MPhil or PhD is strongly preferred

• Ideally, you will have experience within a product-led technology business focused on business information or B2B customer solutions, where Machine Learning is integral to the core product offering. We are particularly interested in candidates who have developed their expertise in product-driven environments, rather than predominantly within IT services or shared-services organisations.

• 10+ years of experience in ML and AI engineering, with at least 2 years in leadership Deep technical expertise in NLP, computer vision, semantic search, generative AI, and production ML systems at scale

• Strong experience building and operating MLOps pipelines, data workflows, and production ML serving infrastructure

• Proven track record of delivering ML solutions end-to-end from concept through production and ongoing optimisation, with measurable business impact

• Significant experience leading and scaling cross-functional ML teams in a product-focused environment

• Demonstrated ability to influence across organisational boundaries and communicate effectively with both technical and non-technical stakeholders

• Advanced Python programming skills and a track record of delivering robust, production-grade ML software

• Proficiency with deep learning frameworks - Transformers, PyTorch, TensorFlow, HuggingFace, PEFT

• Strong experience with cloud infrastructure - AWS, GCP, or Azure - and ML serving platforms including Kubernetes-based inference

• Experience with data pipeline tooling: dbt, Airflow, Kafka, Spark, and modern data stack components

• Strong product mindset - focus on user needs, adoption, and measurable value

 

What we offer:

We are a global fast growing company which offers a variety of opportunities for you to develop your skill set and career. In exchange for your contribution, we can offer you:

• Competitive salary and benefits

• Hybrid working in a team that is passionate about the work we deliver and supporting the development of those that we work with

• A company focus on wellbeing and work life balance including initiatives such as flexible working and mental health support 

 

We want the best talent available, regardless of race, religion, gender, gender reassignment, sexual orientation, marital status, pregnancy, disability or age.