associate qa analyst [t500-21048] Jobs in Hyderabad

associate qa analyst [t500-21048]

engineering  manager-ai/ml Jobs in Hyderabad

engineering  manager-ai/ml

quality assurance automation engineer Jobs in Hyderabad

quality assurance automation engineer

sales quality analyst

senior quality engineer - ai solution and performance testing Jobs in Hyderabad

senior quality engineer - ai solution and performance testing

senior quality engineer ai solution and performance testing

Capgemini

<div>
 
 Capgemini is on the lookout for an experienced Senior Quality Engineer to join our dynamic team focused on AI Solutions and Performance Testing.
 
 
 
 Our client, a leading player in the insurance sector with gross written premiums exceeding US$25 Billion, provides top-tier insurance and financial services to millions of households across the U.S. This role presents an exciting opportunity to work with cutting-edge AI technology in quality assurance, ensuring that our client delivers the best possible products to its users.
 
 
 As a Senior Quality Engineer, you will be pivotal in designing, implementing, and executing automated and performance testing strategies. Your expertise in AI technologies will work in concert with traditional testing methodologies, driving excellence in quality assurance across various applications.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Develop and execute automated test scripts to validate AI-driven solutions using tools like Selenium and Playwright
 </li>
 <li>
 Design and implement comprehensive performance testing strategies leveraging tools such as JMeter and LoadRunner
 </li>
 <li>
 Create and manage test documentation including test plans, test cases, and test scripts
 </li>
 <li>
 Conduct API testing (REST/SOAP) and verify database functionalities against standards
 </li>
 <li>
 Facilitate continuous integration and continuous delivery (CI/CD) environments
 </li>
 <li>
 Collaborate effectively with project teams to identify and resolve defects
 </li>
 <li>
 Stay abreast of trends and innovations in AI and testing methodologies
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 Required Skills :
 
 
 
 Load Runner/Jmeter - Intermediate
 
 
 Dynatrace, AppDynamics or any APM tools - Intermediate
 
 
 Programming skills in Python, Java - Intermediate
 
 
 API testing (REST/SOAP, JSON, XML, MQ) - Entry Level
 
 
 Selenium, Playright and Appium - Entry Level
 
 
 English Proficiency
 
 : Fluent
 
 
 
 Required Branch(es) of study
 
 
 
 Bachelor's degree in computer science, or Information Systems
 
 
 
 
 Benefits
 
 
 
 Competitive compensation and benefits package:
 
 
 <ul>
 <li>
 Competitive salary and performance-based bonuses
 </li>
 <li>
 Comprehensive benefits package
 </li>
 <li>
 Career development and training opportunities
 </li>
 <li>
 Flexible work arrangements (remote and/or office-based)
 </li>
 <li>
 Dynamic and inclusive work culture within a globally renowned group
 </li>
 <li>
 Private Health Insurance
 </li>
 <li>
 Pension Plan
 </li>
 <li>
 Paid Time Off
 </li>
 <li>
 Training &amp; Development
 
 
 </li>
 </ul>
 Note: Benefits differ based on employee level.
 
 
 
 About Capgemini
 
 
 
 Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 340,000 team members in more than 50 countries. With its strong 55-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms. The Group &euro;22.5 billion in revenues in 2023.
 
 
 https://www.capgemini.com/us-en/about-us/who-we-are/
</div>

Senior Quality Engineer - AI Solution and Performance Testing

WaferWire Cloud Technologies

<div>
 
 
 Job Title: Pre-Sales Consultant &ndash; Azure &amp; Data Modernization
 
 
 
 
 Job Location: Hyderabad, India
 
 
 
 
 Worksite: Onsite (100%)
 
 
 
 
 
 
 
 About WCT:
 
 
 
 WaferWire Technology Solutions (WCT) specializes in delivering comprehensive Cloud, Data and AI solutions through Microsoft's technology stack. Our services include Strategic Consulting, Data/AI Estate Modernization, and Cloud Adoption Strategy. We excel in Solution Design encompassing Application, Data, and AI Modernization, as well as Infrastructure Planning and Migrations. Our Operational Readiness services ensure seamless DevOps, ML Ops, AI Ops, and Sec Ops implementation. We focus on Implementation and Deployment of modern applications, continuous Performance Optimization, and future-ready innovations in AI, ML, and security enhancements. Delivering from Redmond-WA, USA, Guadalajara, Mexico and Hyderabad, India, our scalable solutions cater precisely to diverse business requirements and multiple time zones (US time zone alignment).
 
 
 
 
 
 
 About Role:
 
 
 
 We are seeking a dynamic and customer-oriented Pre-Sales Consultant with expertise in Microsoft Azure Cloud, data modernization, and related Microsoft technology stacks. The role involves working closely with sales, solution architects, and delivery teams to design, position, and articulate modern cloud and data transformation solutions for enterprise customers.
 
 
 This position is ideal for someone who enjoys both the technical depth of cloud platforms and the strategic storytelling required to shape customer transformation journeys.
 
 
 
 
 
 
 Responsibilities:
 
 
 <ul>
 <li>
 Participate in client discussions to understand current infrastructure, applications, and data landscape.
 </li>
 <li>
 Design Azure-based architectures for workloads such as data modernization, analytics, and application migration.
 </li>
 <li>
 Create solution blueprints, estimations, and proposals aligned to Microsoft&rsquo;s Cloud Adoption Framework (CAF).
 </li>
 <li>
 Support RFPs, RFIs, and bid responses by providing technical inputs, solution diagrams, and value propositions.
 </li>
 <li>
 Conduct client workshops, demos, and proof-of-concept (PoC) sessions on Azure Data Services (Data Factory, Synapse, Databricks, SQL, etc.).
 </li>
 <li>
 Deliver impactful presentations showcasing modernization journeys from on-prem/VMware/SQL to Azure cloud-native services.
 </li>
 <li>
 Collaborate with account managers to articulate solution benefits and ROI narratives.
 </li>
 <li>
 Collaborate with delivery and practice teams to ensure technical feasibility and smooth handover post-closure.
 </li>
 <li>
 Stay updated on Azure innovations (Fabric, AI/ML integrations, Data Lakehouse models) and align offerings accordingly.
 </li>
 <li>
 Contribute to reusable presales assets such as proposal decks, solution assets, case studies, and success stories.
 </li>
 <li>
 Hands on expertise in using Microsoft office tools &ndash; PowerPoint, Word, Excel and others
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications:
 
 
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Engineering / Computer Science / Information Technology
 </li>
 <li>
 Experience with 3-5 years of experiences as presales consultant
 </li>
 <li>
 Cloud Expertise: Microsoft Azure services (VMs, App Services, AKS, Data Factory, Synapse, SQL Managed Instance, Power BI, Fabric).
 </li>
 <li>
 Data Modernization: Experience in designing data migration or analytics modernization roadmaps.
 </li>
 <li>
 Solutioning Ability: Familiarity with CAF methodology, landing zone design, cost estimation, and migration tooling (Azure Migrate, DMS, HCX).
 </li>
 <li>
 Business Acumen: Ability to translate customer pain points into quantifiable business value and ROI.
 </li>
 <li>
 Soft Skills: Excellent communication, proposal writing, presentation, and stakeholder management.
 </li>
 <li>
 Preferred Exposure: Microsoft Partner ecosystem, pre-sales automation tools, or prior experience in client-facing consulting roles.
 </li>
 <li>
 Azure-related certifications preferred:
 </li>
 </ul>
 
 Microsoft Certified: Azure Solutions Architect Associate (AZ-305)
 
 
 Microsoft Certified: Azure Data Engineer Associate (DP-203) or AI-900 / DP-900
 
 
 
 
 
 
 Equal Employment Opportunity Declaration:
 
 
 
 WCT is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.
 
 
 
</div>

Presales Consultant

<div>
 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.
 
 
 
 Job Description: EY GDS &ndash; Data and Analytics (D&amp;A) &ndash; Senior &ndash; Senior Data Scientist
 
 
 
 
 Role Overview:
 
 We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 3 - 7 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role.
 
 
 
 Responsibilities:
 
 
 
 
 Your technical responsibilities:
 
 
 
 <ul>
 <li>
 Contribute to the design and implementation of state-of-the-art AI solutions.
 </li>
 <li>
 Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI.
 </li>
 <li>
 Collaborate with stakeholders to identify business opportunities and define AI project goals.
 </li>
 <li>
 Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges.
 </li>
 <li>
 Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases.
 </li>
 <li>
 Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities.
 </li>
 <li>
 Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment.
 </li>
 <li>
 Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs.
 </li>
 <li>
 Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs.
 </li>
 <li>
 Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly.
 </li>
 <li>
 Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency.
 </li>
 <li>
 Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases.
 </li>
 <li>
 Ensure compliance with data privacy, security, and ethical considerations in AI applications.
 </li>
 <li>
 Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications.
 
 
 </li>
 </ul>
 
 Requirements:
 
 
 
 <ul>
 <li>
 Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus.
 </li>
 <li>
 Minimum 3-7 years of experience in Data Science and Machine Learning.
 </li>
 <li>
 In-depth knowledge of machine learning, deep learning, and generative AI techniques.
 </li>
 <li>
 Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch.
 </li>
 <li>
 Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models.
 </li>
 <li>
 Familiarity with computer vision techniques for image recognition, object detection, or image generation.
 </li>
 <li>
 Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment.
 </li>
 <li>
 Expertise in data engineering, including data curation, cleaning, and preprocessing.
 </li>
 <li>
 Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems.
 </li>
 <li>
 Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models.
 </li>
 <li>
 Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions.
 </li>
 <li>
 Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels.
 </li>
 <li>
 Understanding of data privacy, security, and ethical considerations in AI applications.
 </li>
 <li>
 Track record of driving innovation and staying updated with the latest AI research and advancements.
 
 
 </li>
 </ul>
 
 Good to Have Skills:
 
 
 
 <ul>
 <li>
 Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems.
 </li>
 <li>
 Utilize optimization tools and techniques, including MIP (Mixed Integer Programming).
 </li>
 <li>
 Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models.
 </li>
 <li>
 Implement CI/CD pipelines for streamlined model deployment and scaling processes.
 </li>
 <li>
 Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines.
 </li>
 <li>
 Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation.
 </li>
 <li>
 Implement monitoring and logging tools to ensure AI model performance and reliability.
 </li>
 <li>
 Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment.
 </li>
 <li>
 Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models.
 
 
 </li>
 </ul>
 
 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.
</div>

EY - GDS Consulting - AI and DATA -Gen AI - Senior

Microsoft

<div>
 The Microsoft CoreAI Post-Training team is dedicated to advancing post-training methods for both OpenAI and open-source models. Their work encompasses continual pre-training, large-scale deep reinforcement learning running on extensive GPU resources, and significant efforts to curate and synthesize training data. In addition, the team employs various fine-tuning approaches to support both research and product development.
 
 
 The team also develops advanced AI technologies that integrate language and multi-modality for a range of Microsoft products. The team is particularly active in developing code-specific models, including those used in Github Copilot and Visual Studio Code, such as code completion model and the software engineering (SWE) agent models. The team has also produced publications as by-products, including work such as LoRA, DeBerTa, Oscar, Rho-1, Florence, and the open-source Phi models.
 
 
 We are looking for a Software Engineer 2 - Machine Learning with significant experience in large-scale model training, data curation, and hands-on coding. You will help in developing LLMs, SLMs, multimodal, and coding models using both proprietary and open-source frameworks. Key responsibilities include improving model quality and training efficiency through advanced techniques and data strategies, and managing the full pipeline from data ingestion, evaluation, to inference.
 
 
 Our team values startup-style efficiency and practical problem-solving. We are seeking a curious, adaptable problem-solver who thrives on continuous learning, embraces changing priorities, and is motivated by creating meaningful impact. Candidates must be self-driven, able to write high-quality code and debug complex systems, document their work clearly, and demonstrate solid experience in shipping ML systems.
 
 
 
 Responsibilities
 
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Collaborate with senior engineers and researchers to build and optimize training and inference pipelines for LLMs, SLMs, multimodal, and code-specific models.
 </li>
 <li>
 Contribute to the deployment and monitoring of models in production environments.
 </li>
 <li>
 Write clean, efficient, and maintainable code for ML systems.
 </li>
 <li>
 Help improve inference performance, reliability, and scalability.
 </li>
 <li>
 Participate in rapid experimentation cycles and support integration with Microsoft products.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 Required Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or master&rsquo;s degree in computer science, Engineering, or a related field, or equivalent practical experience.
 </li>
 <li>
 3+ years of professional experience, including 2+ years with Python and ML frameworks such as PyTorch or TensorFlow.
 </li>
 <li>
 Hands-on experience with training or fine-tuning LLMs or multimodal models.
 </li>
 <li>
 Familiarity with production ML systems and concepts like model serving, caching, batching, and monitoring.
 </li>
 <li>
 Understanding of distributed systems and cloud-based infrastructure.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience with containerization tools (e.g., Docker, Kubernetes).
 </li>
 <li>
 Exposure to MLOps or DevOps practices (CI/CD, automated testing, deployment).
 </li>
 <li>
 Interest in generative AI and open-source model ecosystems.
 </li>
 <li>
 Ability to work in a fast-paced, collaborative environment with a growth mindset.
 </li>
 <li>
 Strong communication and documentation skills.
 
 
 </li>
 </ul>
 #aip #aiplatform #aipidc
 
 
 Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
 
 
 Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
</div>

Software Engineer 2 – Machine Learning

<div>
 Microsoft Silicon, Cloud Hardware, and Infrastructure Engineering (SCHIE) is the team behind Microsoft&rsquo;s expanding Cloud Infrastructure and responsible for powering Microsoft&rsquo;s &ldquo;Intelligent Cloud&rdquo; mission. SCHIE delivers the core infrastructure and foundational technologies for Microsoft's over 200 online businesses including Bing, MSN, Office 365, Xbox Live, Teams, OneDrive, and the Microsoft Azure platform globally with our server and data center infrastructure, security and compliance, operations, globalization, and manageability solutions. Our focus is on smart growth, high efficiency, and delivering a trusted experience to customers and partners worldwide and we are looking for passionate, high-energy engineers to help achieve that mission.
 
 
 The DPU team, within the Azure Hardware Systems &amp; Infrastructure group, brings together state-of-the-art software and hardware expertise to create a highly programmable and high-performance chip with the capability to efficiently handle large data volumes. Thanks to its integrated design, this solution empowers teams to operate with increased agility and deliver significantly superior performance compared to CPU-based alternatives.
 
 
 As a Senior Software Engineer in the DPU Operational Excellence team, you will be involved in designing, building, testing and deploying the tools and agents needed for operational readiness of control and data plane software that runs on DPU&rsquo;s custom-built silicon in a variety of new platforms targeted at Azure compute and networking use-cases. This would entail building a deep understanding of the DPU architecture and the systems built using the DPU, understanding the end-to-end customer workflows, and building the debugging skills required to troubleshoot field issues. You will be responsible for managing the field incidents, maintaining dashboards for active/dormant cases, tracking software/firmware releases, and the fixes being carried in each, and collaborating cross-functionally in the pursuit of case resolution. This is an opportunity to build, test, and support innovative products that will be deployed on a planet scale.
 
 
 Microsoft&rsquo;s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Build, test and deploy innovative tools, and AI agents to reduce time to mitigate production issues.
 </li>
 <li>
 Acts as a Designated Responsible Individual (DRI) and guides other engineers by developing and following the playbook, working on call to monitor system/product/service for degradation, downtime, or interruptions,
 </li>
 <li>
 Alerting stakeholders about status and initiating actions to restore system/product/service for simple and complex problems when appropriate.
 </li>
 <li>
 Guide and help debug field issues. Collaborate cross-functionally and drive debug sessions to arrive at root cause.
 </li>
 <li>
 Maintain dashboards of live/dormant cases and KPIs.
 </li>
 <li>
 Feedback learnings from field issues back into the engineering dev/test process.
 </li>
 <li>
 Embody our culture and values.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 Required/Minimum Qualifications (RQs/MQs)
 
 
 <ul>
 <li>
 Bachelor's Degree in Computer Science, or related technical discipline AND 5+ years technical engineering experience with coding in languages including, but not limited to, C, SQL and / or Python
 </li>
 <li>
 OR equivalent experience
 </li>
 <li>
 5+ Years of previous experience in diagnosing and troubleshooting large scale cloud compute or networking platform features/products.
 
 
 </li>
 </ul>
 
 Additional or Preferred Qualifications (PQs)
 
 
 
 <ul>
 <li>
 Experience with Azure control plane, telemetry, monitoring, diagnostics, reporting infrastructure
 </li>
 <li>
 Experience with complex debug/troubleshooting in both lab and live site situations.
 </li>
 <li>
 Experience with dealing with large-scale data analysis to identify themes and root causes of issues
 </li>
 <li>
 Experience with AI agents to do live site tool automation and analysis
 
 
 </li>
 </ul>
 Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.
 
 
 Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
</div>

Senior Software Engineer

Egen

<div>
 
 Job Description :
 
 
 
 We are seeking a highly motivated and experienced ML Manager/Lead Data Scientist to join our growing ML/GenAI team.
 
 
 You will play a key role in designing, developing and productionalizing ML/GenAI applications by evaluating models, training and/or fine tuning them. As a lead, you require a deep understanding of both machine learning algorithms and software architecture. You need to take ownership of projects from conception to deployment, collaborating with engineers and stakeholders to ensure successful project delivery.
 
 
 
 What we're looking for:
 
 
 
 <ul>
 <li>
 At least 5 years of experience in designing &amp; building ML/AI applications for customer and deploying them into production
 </li>
 <li>
 At least 8 years of Software engineering experience in building Secure, scalable and performant applications for customers
 </li>
 <li>
 At least 2 years of experience leading and mentoring ML/data science teams( 4+ team members)
 </li>
 <li>
 Experience with Document extraction using AI, Conversational AI, Vision AI, NLP or Gen AI
 </li>
 <li>
 Design, develop, and operationalize existing ML models by fine tuning, personalizing it
 </li>
 <li>
 Evaluate machine learning models and perform necessary tuning
 </li>
 <li>
 Develop prompts that instruct LLM to generate relevant and accurate responses
 </li>
 <li>
 Collaborate with data scientists and engineers to analyze and preprocess datasets for prompt development, including data cleaning, transformation, and augmentation
 </li>
 <li>
 Conduct thorough analysis to evaluate LLM responses, iteratively modify prompts to improve LLM performance
 </li>
 <li>
 Lead the end-to-end design and architecture of scalable, reliable, and cost-effective Generative AI solutions. This includes designing RAG (Retrieval-Augmented Generation) pipelines, agentic workflows, and model fine-tuning strategies
 </li>
 <li>
 Hands on customer experience with RAG solution or fine tuning of LLM model
 </li>
 <li>
 Build and deploy scalable machine learning pipelines on GCP or any equivalent cloud platform involving data warehouses, machine learning platforms, dashboards or CRM tools
 </li>
 <li>
 Experience working with the end-to-end steps involving but not limited to data cleaning, exploratory data analysis, dealing outliers, handling imbalances, analyzing data distributions (univariate, bivariate, multivariate), transforming numerical and categorical data into features, feature selection, model selection, model training and deployment
 </li>
 <li>
 Act as the senior-most developer, writing clean, high-quality, and scalable code. This includes building core components for prompt engineering, vector search, data processing, model evaluation, and inference serving
 </li>
 <li>
 Proven experience building and deploying machine learning models in production environments for real life applications
 </li>
 <li>
 Good understanding of natural language processing, computer vision or other deep learning techniques
 </li>
 <li>
 Expertise in Python, Numpy, Pandas and various ML libraries (e.g., XGboost, TensorFlow, PyTorch, Scikit-learn, LangChain)
 </li>
 <li>
 Familiarity with Google Cloud or any other Cloud Platform and its machine learning services
 </li>
 <li>
 Excellent communication, collaboration, and problem-solving skills
 
 
 
 </li>
 </ul>
 
 Good to Have
 
 
 
 <ul>
 <li>
 Google Cloud Certified Professional Machine Learning or TensorFlow Certified Developer certifications or equivalent
 </li>
 <li>
 Experience of working with one or more public cloud platforms - namely GCP, AWS or Azure
 </li>
 <li>
 Experience with AutoML and vision techniques
 </li>
 <li>
 Master&rsquo;s degree in statistics, machine learning or related fields
 
 
 
 </li>
 </ul>
 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
</div>

Engineering  Manager-AI/ML

Software Engineer, Power and Performance Automation

Explore 272+ Senior quality engineer ai solution and performance testing in Hyderabad this November. Find roles across top companies and apply now to boost your career.