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Onclusive संचार टीमों, ब्रांडों और एजेंसियों के लिए मीडिया मॉनिटरिंग और जनसंपर्क मापन सॉफ़्टवेयर उपलब्ध कराता है। इसका Analyst प्लेटफ़ॉर्म वैश्विक न्यूज़ क्रॉलर के माध्यम से डिजिटल, प्रिंट, प्रसारण और सोशल मीडिया से कवरेज एकत्र करता है, जिससे उपयोगकर्ता अर्जित और स्वामित्व वाले मीडिया पर नज़र रख सकते हैं, संचार के प्रभाव को माप सकते हैं और अभियानों से जुड़ी अंतर्दृष्टि पहचान सकते हैं। कंपनी रिपोर्टिंग, प्रेसरूम प्रबंधन और मीडिया संबंधों में सहायता के लिए सोशल लिसनिंग, एनालिटिक्स, प्रेस संपर्क प्रबंधन, मीडिया डेटाबेस, Data-as-a-Service और परामर्श सेवाएँ भी प्रदान करती है। Onclusive अंतरराष्ट्रीय स्तर पर एंटरप्राइज़ और एजेंसी ग्राहकों की सेवा करता है तथा परामर्श, मार्केटिंग और SaaS क्षेत्रों में कार्य करता है।
Director of Machine Learning at Onclusive (Hybrid, India)
Lead production NLP, computer vision, and generative AI for Onclusive’s media analytics platform. Set ML strategy, strengthen MLOps, and build high-performing AI teams.
विवरण
- Own Onclusive’s long-term AI/ML strategy in line with product plans and business priorities
- Find valuable AI/ML opportunities and work with product and engineering teams to bring them to market
- Act as a senior AI/ML authority, promoting current methods and sound engineering practices
- Turn business challenges into AI products with clearly defined measures of success
- Guide the full ML lifecycle, from research and design through experimentation, validation, deployment, and improvement
- Build and mature MLOps capabilities that support reproducibility, reliability, observability, cost control, and dependable model delivery
- Set architecture standards for production ML, data pipelines, embedding systems, self-hosted models, and agentic AI
- Promote strong coding practices, peer review, version control, CI/CD, testing, and documentation
- Lead Agile execution through sprint planning, quarterly OKRs, technical reviews, and retrospectives
- Oversee AI data pipelines, including batch workloads, event-driven systems, and feedback mechanisms
- Evaluate system designs and steer key architectural choices
- Coach and develop ML engineers, data scientists, and platform engineers
- Grow a high-performing AI/ML organisation while sustaining a strong engineering culture
- Set clear expectations, give constructive feedback, and support individual career development
- Lead a thorough, effective interview and hiring process
- Work with product management on AI/ML strategy, prioritisation, roadmaps, and delivery
- Partner with data platform, security, and compliance teams to meet GDPR, EU AI Act, and SOC2 obligations
- Keep leadership and the wider organisation informed
- Represent the AI/ML function in company discussions about strategy, governance, and innovation
आवश्यकताएँ
- Advanced study in Computer Science, Applied Mathematics, Statistics, or a related technical discipline, or equivalent industry expertise
- An MPhil or PhD is strongly preferred
- At least 10 years of professional experience in ML and AI engineering
- A minimum of two years in a leadership role
- Expertise in NLP, computer vision, semantic search, generative AI, and large-scale production ML systems
- Hands-on experience designing and running MLOps pipelines, data workflows, and production model-serving infrastructure
- Demonstrated success taking ML solutions from initial concept into production and ongoing optimisation with measurable business results
- Substantial experience managing and expanding cross-functional ML teams in a product-led organisation
- Ability to build alignment across teams and communicate clearly with both technical and non-technical audiences
- Advanced proficiency in Python
- Working knowledge of Transformers, PyTorch, TensorFlow, HuggingFace, and PEFT
- Strong cloud experience with AWS, GCP, or Azure, plus Kubernetes-based inference platforms
- Experience using dbt, Airflow, Kafka, Spark, and modern data-platform technologies
- A strong product orientation centred on user needs, adoption, and measurable outcomes
- Experience owning products and roadmaps, ideally including Product Owner responsibilities
लाभ
- Competitive pay and benefits package
- Hybrid work arrangement
- Flexible working options
- Mental health resources
- Wellbeing and work-life balance programmes
- Opportunities to expand skills and progress professionally
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