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Sr. Engineering Manager , Machine Learning

5 - 9 years

0 Lacs

karnataka

Posted:3 days ago| Platform: Shine logo

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Skills Required

machine learning python aws azure gcp spark fraud detection personalization distributed computing ml models aiml scikitlearn tensorflow pytorch mlops graphbased ml ranking algorithms

Work Mode

On-site

Job Type

Full Time

Job Description

As a Senior Engineering Manager, Machine Learning at Adobe, your role involves leading a high-impact team dedicated to building and deploying brand-new ML solutions. You will guide the team through the full lifecycle of machine learning projects, collaborate with various teams to innovate custom products, and contribute to the ML strategy on the Genuine Engineering team. **Key Responsibilities:** - Lead, mentor, and grow a team of ML engineers to develop and deploy pioneering ML models. - Own the end-to-end execution of ML projects, from research and prototyping to production deployment. - Collaborate with product teams to identify AI/ML opportunities and define technical roadmaps. - Ensure ML models are scalable, efficient, accurate, and aligned with business goals. - Adopt standard methodologies in ML model training, evaluation, and monitoring for high performance and reliability. - Work with infrastructure teams to optimize deployment and inference for ML models. - Stay ahead of advancements in AI/ML and bring innovative solutions to Adobe's products. - Champion responsible AI practices, ensuring fairness, interpretability, and robustness in ML models. - Partner with leadership to align ML strategy with business objectives and contribute to long-term AI initiatives. **Minimum Qualifications:** - Proven track record in software engineering, with at least 5 years in machine learning and 3+ years leading teams. - Experience in unsupervised and semi-supervised learning for anomaly detection using techniques like auto encoders, isolation forests, and graph-based fraud detection. - Hands-on experience with ML frameworks such as Scikit-Learn, TensorFlow, and PyTorch. - Proficiency in Python and experience in cloud platforms like AWS, Azure, or GCP. - Strong background in MLOps, model optimization, and deploying ML models at scale. - Proven ability to mentor engineers and build high-performing teams. - Experience in developing large-scale data pipelines in Spark. - Strong problem-solving skills and ability to navigate sophisticated technical challenges. **Preferred Qualifications:** - Knowledge of graph-based ML, personalization, and ranking algorithms. - Familiarity with distributed computing frameworks like Spark, Ray, or Dask. - Experience in bringing research into production in the domain of fraud detection.,

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