5 Model Optimization Jobs

We are seeking an experienced Gen AI and LLM Developer to design, develop, and deploy generative AI models and large language models (LLMs) for advanced natural language processing (NLP) tasks. The ideal candidate will have 6-9 years of experience with LLM architectures (e.g., GPT, BERT), deep learning frameworks (PyTorch, TensorFlow), and cloud platforms (AWS, GCP, Azure). Responsibilities include training and fine-tuning models, optimizing for performance, collaborating with cross-functional teams, and staying updated on the latest AI trends. Strong technical skills in Python, NLP techniques, model optimization, and distributed training are essential.Experience designing scalable system with Generative AI" and "Exposure to full stack development on .net or Java based platform

We are a pioneering company dedicated to Revolutionizing autism with AI-driven solutions. Role: Develop AI models using Python and TensorFlow Implement machine learning algorithms Collaborate with data scientists to enhance AI systems Required Candidate profile Optimize AI solutions for performance Integrate AI with business applications Stay updated on AI advancements.

Hiring for Financial Analyst (DCF Modeling Expert) for Delhi Salary up to 10 LPA + 5 Days working + Sat & Sun Fixed Off. Immediate Joiner & 15 Days Notice Only/- Call HR Arpita TO Schedule Your Interview @ 9257030238 DROP YOUR RESUME:- arpita@virtueplacement.com Key Responsibilities:- Argus Enterprise Expertise: Utilize Argus Enterprise extensively to develop, maintain, and refine financial models for real estate assets. Ensure accuracy in cash-flow projections and valuations. DCF Modeling: Build and enhance Discounted Cash Flow (DCF) models to analyze investment opportunities, asset performance, and future cash flows. Model Optimization: Regularly update financial models in Argus to reflect changing market conditions and investment strategies. Market Research: Conduct detailed market analysis for multifamily assets, property comparables, and industry trends to support financial modeling. Financial Reporting: Prepare and present financial reports and insights based on DCF and Argus analyses for senior management and clients. Collaboration: Work closely with internal teams during acquisitions, dispositions, and development projects to provide analytical support. Investment Performance Evaluation: Analyze investment performance using key financial metrics (IRR, Cash-on-Cash returns, etc.) and integrate insights into financial models. Required Skills & Qualifications:- Education: Bachelors degree in Finance, Real Estate, Business, Economics, or a related field. Experience: 3-5 years of experience in financial modeling, real estate finance, or investment analysis. (Experience in Equity Research, Investment Banking, or Private Equity is a plus). Argus Enterprise Expertise: Strong hands-on experience with Argus Enterprise for financial modeling. DCF Proficiency: Deep understanding of Discounted Cash Flow (DCF) modeling and financial scenario analysis. Analytical Skills: Strong problem-solving abilities with a keen eye for financial insights. Communication: Excellent verbal and written communication skills for presenting financial concepts to stakeholders. Organizational Ability: Ability to manage multiple priorities in a fast-paced environment. Collaboration: Ability to work effectively in a team-oriented environment. Immediate Joiner & 15 Days Notice Only/- Preferred Qualifications:- Software Proficiency: Advanced skills in Microsoft Excel for financial modeling. Certifications: CFA, CA, or FRM (preferred but not mandatory). Advanced Degree: Masters degree in Finance, Business, Real Estate, or Economics is a plus. Additional Software Knowledge: Familiarity with Yardi Voyager, Google Earth, and other real estate software is an advantage. Immediate Joiner & 15 Days Notice Only/- Call HR Arpita TO Schedule Your Interview @ 9257030238 DROP YOUR RESUME:- arpita@virtueplacement.com Note Applications SENT TO ANY Other Email Address WILL NOT BE Entertained.

Develop and optimize AI models for business-specific use cases. Perform data analysis, feature engineering, and model training. Implement and fine-tune NLP and machine learning algorithms. Evaluate model performance and ensure continuous improvements. Work with engineers to deploy models in production environments.

Key Responsibilities: Design & Develop AI Models : Create and implement machine learning models and algorithms to solve business challenges. Data Processing & Analysis : Analyze large datasets, preprocess data, and apply statistical techniques to improve model accuracy. Deep Learning & NLP : Work with advanced AI techniques such as neural networks, reinforcement learning, and natural language processing to build intelligent systems. Model Optimization : Optimize models for performance, scalability, and efficiency using techniques such as hyperparameter tuning and model deployment. Collaboration : Collaborate with software engineers, data scientists, and business teams to integrate AI solutions into applications and platforms. Testing & Validation : Test and validate AI models, ensuring their effectiveness, and continuously improve them based on feedback and new data. Documentation : Write clear documentation for models, algorithms, and code to ensure maintainability and scalability. Research : Stay updated with the latest advancements in AI technologies and research to apply cutting-edge techniques. Required Skills and Experience: Model Hosting and Deployment: Strong experience with deploying and managing machine learning models in production environments. Server Infrastructure: Proficient in building and managing servers to host and serve models for scalable access. APIs: Expertise in developing and deploying RESTful APIs for model inference. Redis & Celery: Solid experience with Redis for caching and Celery for task management and background job processing. PostgreSQL: Strong knowledge of PostgreSQL for data management and querying in the context of ML applications. Model Repositories: Experience with version control and repositories for machine learning models, including integration with Git or similar platforms. Cloud Platforms: Experience with cloud services (e.g., AWS, GCP, Azure) for deploying and managing models at scale. Preferred Skills: Familiar with CI/CD pipelines for AI models to ensure automated testing, deployment, and updates. Experience with containerization technologies such as Docker and Kubernetes for deployment and orchestration. Familiarity with frameworks like TensorFlow Serving, TorchServe, or similar for serving models in production. Knowledge of model monitoring tools and logging frameworks. Ability to work in a fast-paced, collaborative environment with cross-functional teams. Knowledge in consumer and server grade GPU to handle CUDA compatability issues.