... develop, and deploy advanced machine learning models and AI algorithms to address business challenges. Lead initiatives in developing and fine-tuning Large Language Models (LLMs) and other AI/ML frameworks. Implement MLOps best practices for model deployment, monitoring, and maintenance to ensure scalable and reliable AI solutions. ...
... experience and passion for selling technology solutions. Support & partner with sales executives to plan, prepare & execute on strategic deals in complex sales cycles Model the finance business case associated with each sales opportunity Effectively communicate client needs to the technical/R&D team for future product enhancements ...
... production-ready solutions. What You'll D oDesign and build Bayesian Marketing Mix Models (MMM) from the ground up using PyMC or Stan - Develop hierarchical Bayesian models capable of handling sparse and multi-level marketing data - Implement chained and multi-stage modeling architectures with proper uncertainty propagation using ...
... researching new tools and technologies to keep our software development eco-system on the cutting edge for embracing microservices development and deployment models. Maintain code quality through best practices, unit testing and test automation. Diagnosing and improving application or system performance and optimizing/improving ...
... Cassandra) Depending on Client Needs (Demand Specific / Program Driven) These are selectively required based on client industry, program type, or engagement model and should be treated as optional add ons in JD postings. Client / Industry Specific Banking / Financial Services domain experience Knowledge of regulatory, ...
... AI-powered data analytics solutions for business intelligence, forecasting, and optimization. Leverage AI tools to automate data cleansing, feature engineering, model building, and visualization. Design and conduct advanced statistical analyses and machine learning models (supervised, unsupervised, NLP, etc.). Collaborate ...
... and partnership development. Commercial reasoning. Professional writing. Relationship building. Understanding business needs. Can explain a company's business model. AI can help organise information. AI can draft outreach. But it cannot replace commercial judgement. You believe volume automatically equals sales. Subject ...
... learn the ICP and the current account list, sit in on sales calls, and review what has worked and what has not. By 45-60 days: deliver a revised account tiering model, a buying committee map, and your first campaign brief. 3 to 7 years in B2B marketing, with at least 2 of those running account-based or targeted campaigns into ...
... Advertising works together to understand your business challenges and the way your customers think about your business. We strive to challenge the traditional model to make brands more innovative in the quest to reach new audiences. We believe there is no single template that can be applied to every story. Research is the ...
... regulatory requirements throughout the project lifecycle. signalling, SCADA, telecom, traction power) into a cohesive rail system. Conduct system-level analysis, modelling, and simulations to validate performance and safety. Participate in design reviews, hazard analysis, and risk assessments. Support testing and commissioning ...
... locating lighting - Fixtures, Support requirement. - Hands on experience in REVIT electrical - Preparation and checking of Material Take Off. (MTO) - Updating the model as per vendor drawings. - Working on Micro station & Auto CAD. - Extract drawing in MicroStation - Should be able to work on the inputs in the form of sketch ...
... potential partnerships, acquisitions, and new market entries. - Assess the viability and potential return on investment for proposed initiatives. 4. Business Model Innovation: - Develop and refine business models to support the launch and scaling of new products and services. - Ensure business models are robust, scalable, ...
... and hands-on experience with Transformer-based Language Models like BERT, Llama, Qwen, Gemma, DeepSeek, etc In-depth familiarity with LLM training concepts, model inference optimizations, GPUs, etc Experience with ML and Deep Learning model deployments using REST API, Docker, Kubernetes, etc Good problem-solving skills ...
... Engineer Specialization: Data Engineering | Databricks | Lakehouse | Data Platforms | AI-Ready Data Experience: 5+ Years Location: BNG | HYD | PUN | MUM | GGN Work Model: Hybrid What We're Looking For Mandatory-Strong hands-on experience required: - Databricks – with practical experience building production data platforms and ...
... cutting-edge manufacturing, turning abstract ideas into realities that transform the world for good. Your impact The candidate will be responsible for designing, modeling, and coordinating electrical systems for industrial facilities and data center projects, ensuring compliance with project specifications, codes, and standards. ...
... Following up and driving conversions - Managing pipeline & CRM What You'll Sell - AI-based Trading Course (50K ticket size) - Trading App with recurring earning model This is not basic selling - you're dealing with serious buyers & real money conversations Who Should Apply - 1 year - 3 years of sales experience - High-ticket ...
... Monitor resource utilization and productivity index of the department Monitor resource workload and approve overtime hours Manage leaves of the resources for FTE model Manage free pool of resources and allocate them internal projects/ R&D tasks Maintain onboarding and offboarding of resources as per project planning Administration ...
... Workflows: Architect and develop advanced Retrieval-Augmented Generation (RAG) pipelines, implement Agentic AI workflows using multi-agent frameworks, and integrate Model Context Protocol (MCP) servers and clients. MLOps/LLMOps Engineering: Design and maintain production-ready MLOps pipelines (CI/CD, automated testing, model registry, ...
... hustlers building the next generation of Machine Learning platform & services. You will develop training and deployment pipelines for machine learning, implement model compression algorithms, and productionize machine learning research solving challenging business problems. Key Responsibilities: Design and develop generative ...
... platforms; exposure to relational databases, MongoDB, Redis, ClickHouse or equivalent data technologies is beneficial. - Understanding of machine learning, NLP, model integration, model evaluation, data preparation and feature engineering. - Working knowledge of Docker, Kubernetes or OpenShift, Git, GitHub Actions or GitLab ...