ai and a - machine learning engineer - vg - w4 - cdao0230

hro (recruitment operations)-process developer/ management trainee/assistant manager

business risk consultant

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 At EY, you&rsquo;ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we&rsquo;re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.
 
 
 
 Title: Manager II, Machine Learning Engineer
 
 
 
 EY is a global leader in assurance, tax, transaction and advisory services. Technology is at the heart of what we do and deliver at EY. Technology solutions are integrated in the client services we deliver and are key to our innovation as an organization.
 
 
 Fueled by strategic investment in technology and innovation, Client Technology seeks to drive growth opportunities and solve complex business problems for our clients through building a robust platform for business and powerful product engine that are vital to innovation at scale. As part of Client Technology, you&rsquo;ll work with technologists and business experts, blending EY&rsquo;s deep industry knowledge and innovative ideas with our platforms, capabilities, and technical expertise. As a catalyst for change and growth, you&rsquo;ll be at the forefront of integrating emerging technologies from AI to Data Analytics into every corner of what we do at EY. That means more growth for you, exciting learning opportunities, career choices, and the chance to make a real impact.
 
 
 
 EY Technology:
 
 
 
 Technology has always been at the heart of what we do and deliver at EY. We need technology to keep an organization the size of ours working efficiently. We have 250,000 people in more than 140 countries, all of whom rely on secure technology to be able to do their job every single day. Everything from the laptops we use, to the ability to work remotely on our mobile devices and connecting our people and our clients, to enabling hundreds of internal tools and external solutions delivered to our clients. Technology solutions are integrated in the client services we deliver and is key to us being more innovative as an organization.
 
 
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 EY Technology supports our technology needs through three business units:
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 Client Technology (CT) - focuses on developing new technology services for our clients. It enables EY to identify new technology-based opportunities faster and pursue those opportunities more rapidly.
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 Enterprise Workplace Technology (EWT) &ndash; EWT supports our Core Business Services functions and will deliver fit-for-purpose technology infrastructure at the cheapest possible cost for quality services. EWT will also support our internal technology needs by focusing on a better user experience.
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 Information Security (Info Sec) - Info Sec prevents, detects, responds and mitigates cyber-risk, protecting EY and client data, and our information management systems.
 
 
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 The opportunity
 
 
 
 This role will be managing a team of machine learning engineers responsible for the development and programming of machine learning integrated software algorithms. Supports the continuous evolution and strategy of machine learning engineer program. This role also includes creating data mining architectures, applying data science methodologies, and researching emerging techniques to identify trends and inform business decisions.
 
 
 
 Your Key Responsibilities
 
 
 
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 Hires, evaluates, and supervises crew. Provides guidance and training as necessary to develop crew. Sets performance standards, reviews performance, and makes informed compensation decisions in accordance with all applicable Human Resources policies and procedures.
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 Oversees complex data pipelines and implements data engineering design principles for iterative data pipeline development to drive scale and efficiency.
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 Monitors existing data and model pipelines in a production environment. Identifies and diagnoses data inconsistencies and errors, documents assumptions, and forages to fill data gaps. Applies knowledge of experimental methodologies, statistics, optimization, probability theory, and machine learning concepts to create self-running artificial intelligence (AI) systems to automate predictive models.
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 Collaborates with other data science teams to review model ready dataset document/feature documentation.
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 Partners with data science teams to understand data requirements. Oversees detailed analysis of raw data sources for data quality, applies business context, and model development needs. Drives efficiency through the use of data discovery tools.
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 Engages with internal stakeholders to understand and probe business processes in order to develop hypotheses. Brings structure to requests and translates requirements into an analytic approach. Supports ongoing business planning and departmental prioritization activities.
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 Guides model monitoring scripts as needed. Diagnoses root causes based on model monitoring alerts and triages issues. Coordinates and plans response to model monitoring alerts and resolves issues.
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 Executes operational plans to achieve department objectives. Collaborates with department or functional heads in planning, developing, and executing near-term goals.
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 Prepares, reviews, and delivers insight presentations and action recommendations. Communicates complex analytical findings and implications to business leaders.
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 Participates in special projects and performs other duties as assigned.
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 Develops scalable data mining strategies and analytical models to uncover hidden patterns and improve decision-making processes across domains.
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 Applies domain-specific data analysis techniques in sectors like marketing, supply chain, or scientific research to deliver strategic impact.
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 Explores and integrates emerging data science frameworks and tools to enhance analytical maturity and model performance across the enterprise.
 
 
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 Skills And Attributes For Success
 
 
 
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 A team player with strong analytical, communication and interpersonal skills
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 Constantly updating yourself about new technologies in the market
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 A winning personality and the ability to become a trusted advisor to the stakeholders
 
 
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 To qualify for the role, you must have
 
 
 
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 Minimum 8 years of experience in data science, data engineering, or machine learning roles
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 Bachelor&rsquo;s degree (B.E./B.Tech) in Data Science, Computer Science, or Applied Mathematics; Master&rsquo;s degree/Diploma preferred in relevant fields
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 Strong hands-on experience in pipeline design, model monitoring, AI/ML implementation, stakeholder collaboration, and analytical storytelling.
 
 
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 Ideally, you&rsquo;ll also have
 
 
 
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 Strong verbal and written communication, facilitation, relationship-building, presentation and negotiation skills.
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 Be highly flexible, adaptable, and creative.
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 Comfortable interacting with senior executives (within the firm and at the client)
 
 
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 What We Look For
 
 
 
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 Strong teamwork, work ethic, product mindset, client centricity and a relentless commitment to EY values.
 
 
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 What Working At EY Offers
 
 
 
 We offer a competitive remuneration package where you&rsquo;ll be rewarded for your individual and team performance. Our comprehensive Total Rewards package includes support for flexible working and career development, and with FlexEY you can select benefits that suit your needs, covering holidays, health and well-being, insurance, savings and a wide range of discounts, offers and promotions. Plus, we offer:
 
 
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 Support, coaching and feedback from some of the most engaging colleagues around
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 Opportunities to develop new skills and progress your career
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 The freedom and flexibility to handle your role in a way that&rsquo;s right for you
 
 
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 EY | Building a better working world
 
 
 
 EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.
 
 
 Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.
 
 
 Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.
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AI And A - Machine Learning Engineer - VG - W4 - CDAO0230

Blumetra Solutions

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 Work Location: Hyderabad (Hybrid Model)
 
 
 
 
 Prestige Skytech, Financial District
 
 
 
 
 Experience: 5 - 8 years
 
 
 
 
 Mandatory Skills: AI, ML, RAG, LLM
 
 
 
 
 Key Responsibilities
 
 
 
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 Agentic AI Development:
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 Build, customize, and deploy AI agents using frameworks like LangChain, AutoGen, CrewAI, and Haystack.
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 Enable agent reasoning, planning, and tool-use for complex tasks.
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 RAG Pipeline Design:
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 Implement and optimize RAG pipelines for enterprise-scale knowledge retrieval.
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 Work with vector databases (Pinecone, FAISS, Weaviate, Milvus) to manage embeddings and context injection.
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 Fine-tune retrieval strategies, chunking logic, and metadata tagging for high-quality responses.
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 Prompt Engineering &amp; LLM Integration:
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 Develop structured prompts, context-aware query chains, and workflows for LLMs (OpenAI, Anthropic, Llama, Mistral, etc.).
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 Integrate RAG-enabled LLMs into APIs, chatbots, and enterprise applications.
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 Automation &amp; Platform Development:
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 Create orchestration pipelines for AI agents and RAG workflows.
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 Contribute to building internal AI platforms, dashboards, and monitoring systems.
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 Experimentation &amp; Research:
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 Stay current with new developments in RAG, multi-agent systems, and reasoning models.
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 Rapidly prototype AI solutions to demonstrate value to business teams.
 
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 Required Skills
 
 
 
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 Programming: Strong in Python; familiarity with JavaScript/TypeScript or Go is a plus.
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 LLM Frameworks: Experience or coursework in LangChain, LlamaIndex, Haystack, or AutoGen.
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 RAG Expertise: Understanding of RAG concepts, document indexing, embeddings, retrieval strategies, and vector DBs.
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 Databases: PostgreSQL/MySQL for structured data; Pinecone, Weaviate, Milvus, FAISS for vectors.
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 APIs &amp; Cloud: Knowledge of REST/GraphQL APIs and cloud services (AWS/GCP/Azure).
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 Version Control: Git, GitHub/GitLab, and CI/CD pipelines.
 
 
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 Preferred Skills (Good-to-Have)
 
 
 
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 Familiarity with LangGraph and other agent orchestration libraries.
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 Exposure to multi-agent collaboration patterns and reasoning models (OpenAI o1, DeepSeek-R1).
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 Knowledge of document preprocessing, semantic search, and hybrid retrieval.
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 Understanding of MLOps for deploying and monitoring AI pipelines.
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 Experience with Docker, Kubernetes, and distributed systems.
 
 
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 Qualifications
 
 
 
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 Bachelor&rsquo;s degree in Computer Science, Engineering, AI/ML, or related field.
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 Strong analytical skills, eagerness to experiment, and enthusiasm to learn cutting-edge AI tools.
 
 
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 Skills: llm,ai,rag,agents,ml
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AI Engineer

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AI And A - Machine Learning Engineer - VG - W4 - CDAO0230

AI Engineer