Machine Learning Engineer – Senior Consultant

Deloitte’s Cloud Machine Learning (ML) offering combines the power of our Cloud, ML, and Analytics to accelerate the delivery of value for our clients, all using NexGen capabilities. Our clients are looking for ways to integrate more automation into business processes and are ready to adopt public cloud to transform their organization. We are looking for smart AIML Engineers who have experience in working with large-scale data ecosystems including data lake, data management, governance. We are seeking experienced architects and engineers who can apply the latest techniques to help our clients in the integration of structured and unstructured data to generate insights leveraging cloud-based platforms. Work you’ll do In partnership with other leaders in the firm, you will focus on understanding requirements, designing and deploying leading AIML engineering solutions and, as a key member of our engineering practice solve tough problems and ensure success in designing and building complex world-class applications with automation on public cloud. bull Engage and consult with clients on foundational Data, AI, ML, Analytics requirements bull Build PoCs with hands on efforts that demonstrate understanding of requirements and knowledge of AIML tools bull Translate POCs into production grade code with appropriate guardrails and reviews bull Design the AIML-powered Data architecture with the security focus and tools baked in by default bull Leverage our deep relationships and partner programs to maintain and enhance our leading edge Data, AI, ML, Analytics and public cloud skills – participate in trusted tester programs and alphabetas. bull Assist in developing our AIML community of practice by sharing your knowledge and experience with your peers and apprentices. bull Collaborate with our partners, developers and engineers to build repeatable AIML powered cloud-native solutions that accelerate our clients’ path to value. bull Author or otherwise contribute to AIML customer-facing publications such as podcasts, blogs, and whitepapers The team CBO Cloud Engineering Team The US Cloud Engineering Offering focuses on enabling our client’s end-to-end journey from On-Premise to Cloud, with opportunities in the areas of Cloud Strategy and Op Model Transformation, Cloud Development Integration, Cloud Migration, and Cloud Infrastructure Managed Services. Cloud Engineering supports our clients as they improve agility and resilience and identifies opportunities to reduce IT operations spend through automation by enabling Cloud. We accelerate our clients toward a technology-driven future, leveraging vendor solutions, Deloitte-developed software products, tools, and accelerators. Qualifications bull 6+ years of experience as a data engineer, with large-scale data ecosystems including data lake, data management, governance and the integration of structured and unstructured data to generate insights leveraging cloud-based platforms bull Experience with performing big data transformation and experience or familiarity working with distributed computing such as Spark bull Experience with programming languages Python, Scala, R, Java etc. bull 5+ years of experience with building and deploying ML-based solutions and proficiency in common machine learning frameworks such as TensorFlow, Keras, scikit-learn, Pytorch and ONNX bull Experience with designing, building, and maintaining production-grade ML and DL models, machine learning workflows and pipelines bull Familiarity with docker containers and Kubernetes orchestration bull Experience with deploying ML Solutions on AWS Google Cloud Platform or Azure cloud platforms and exposure to cloud services necessary to build end to end pipeline bull Experience with building and deploying Deep learning solutions in the field of computer vision and Natural Language processing bull Good understanding and experience with MLOPs bull Should be able to build distributed, scalable, and reliable data pipelines that ingest and process data at scale and in real-time to feed machine learning algorithms and pipelines bull Should be able work with an agile team that includes members with cross-functional skills bull Experience with dashboard tools such as Tableau or Power BI to visualize model results and evaluate bull Good understanding and experience building reusable design patterns bull Good understanding and knowledge of DevOps pipelines and IaC technologies such as Terraform bull Excellent listening, interpersonal, written, and oral communication skills. bull Skilled at working within a team-oriented, collaborative environment. Required 6-8 Years of experience Bachelor’s degree in Computer Science, Mathematics, related technical field or equivalent practical experience Travel up to 50 (While 50 of travel is a requirement of the role, due to COVID-19, non-essential travel has been suspended until further notice.) Limited immigration sponsorship may be available How you’ll grow At Deloitte, our professional development plan focuses on helping people at every level of their career to identify and use their strengths to do their best work every day. From entry-level employees to senior leaders, we believe there’s always room to learn. We offer opportunities to help sharpen skills in addition to hands-on experience in the global, fast-changing business world. From on-the-job learning experiences to formal development programs at Deloitte University, our professionals have a variety of opportunities to continue to grow throughout their career. Explore Deloitte University, Th e Leadership Center. INDCONS

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