41 Openai Apis Jobs - Page 2

We are looking for a skilled and motivated Data Scientist with a strong background in backend development and AI/ML engineering. The ideal candidate should have experience in constructing, deploying, and expanding machine learning solutions using Python and modern ML frameworks. Responsibilities: - Develop and implement machine learning models, including advanced architectures like Large Language Models (LLMs). - Collaborate with various teams to create scalable AI-driven solutions using sound software engineering principles. - Utilize Python and object-oriented programming to build efficient, maintainable, and production-grade ML pipelines. - Work with popular ML frameworks such as TensorFlow, PyTorch, and Scikit-learn for model development and testing. - Integrate AI/ML models into applications via RESTful APIs while ensuring performance, scalability, and reliability. - Use tools like Hugging Face, LangChain, and OpenAI APIs for NLP and generative AI model development. - Manage containerized services using Docker for seamless deployment and reproducibility of ML solutions. - Follow best practices in version control (Git) and software development lifecycles to support collaborative and agile workflows. - Develop and maintain relational databases (e.g., MySQL, PostgreSQL, Oracle) to support data-driven applications. - Contribute to microservices-based architectures for AI/ML systems. - Apply agent communication protocols and multi-agent system design in relevant AI applications. - Analyze large datasets, extract actionable insights, and continuously improve models. Required Skills and Qualifications: - Minimum 4 years of experience in data science, machine learning, or backend development. - Proficiency in Python and solid foundations in object-oriented programming. - Hands-on experience with the entire machine learning model lifecycle, from training to production deployment and monitoring. - Understanding of scalable system design and microservices architecture. - Strong problem-solving skills, attention to detail, and knowledge of data structures and algorithms. - Excellent communication and collaboration abilities, with a knack for working in a dynamic team setting. Preferred Qualifications: - Expertise in Generative AI, particularly with Large Language Models (LLMs) like GPT and LLaMA. - Proficiency in prompt engineering, fine-tuning LLMs, and evaluating AI model performance. - Familiarity with AI system architecture, including orchestration frameworks and agent-based designs. - Experience with advanced AI tools, platforms, and APIs for scalable systems. - Strong communication skills and proven track record of effective collaboration in cross-disciplinary teams. - Knowledge of ethical AI principles, including model interpretability, fairness, responsible AI deployment, and ongoing monitoring.,

We are seeking a dedicated Data Scientist with a strong background in Natural Language Processing (NLP) and expertise in Large Language Models (LLMs). As a part of our team, you will play a crucial role in the development, optimization, and implementation of open-source and API-based LLMs to address real-world challenges. Your primary responsibilities will revolve around constructing resilient GenAI pipelines, innovative internal tools, and customer-centric applications. This position offers you a remarkable chance to be at the forefront of Artificial Intelligence advancements and make significant contributions to the evolution of intelligent systems through the utilization of Retrieval-Augmented Generation (RAG) frameworks, vector databases, and real-time inference APIs. Your responsibilities will include fine-tuning and enhancing open-source LLMs tailored to specific business sectors, building and managing RAG pipelines utilizing tools like LangChain, FAISS, and ChromaDB, creating LLM-powered APIs for applications like chatbots, Q&A systems, summarization, and classification, as well as designing effective prompt templates and implementing chaining strategies to augment LLM performance across diverse contexts. To excel in this role, you must possess a deep understanding of NLP principles and advanced deep learning techniques for text data, hands-on experience with LLM frameworks like Hugging Face Transformers or OpenAI APIs, familiarity with tools such as LangChain, FAISS, and ChromaDB, proficiency in developing REST APIs for machine learning models, proficiency in Python along with expertise in libraries such as PyTorch or TensorFlow, and a solid grasp of data structures, embedding techniques, and vector search systems. Desirable qualifications include prior experience in LLM fine-tuning and evaluation, exposure to cloud-based ML deployment on platforms like AWS, GCP, or Azure, and a background in information retrieval, question answering, or semantic search. If you are passionate about generative AI and eager to work with cutting-edge NLP and LLM technologies, we are excited to connect with you.,

As a Data Scientist at Objectways located in Chennai, you will have the opportunity to be part of a team that is driving AI innovation and solving real-world problems by leveraging cutting-edge machine learning and reasoning technologies. Our projects are ambitious and diverse, ranging from agent trajectory prediction to complex reasoning systems, multimodal intelligence, and preference-based learning. We are looking for a talented individual like you who is eager to explore the boundaries of applied AI. In this role, you will be responsible for designing and developing machine learning models for both structured and unstructured data. You will work on agent trajectory prediction, complex reasoning, preference ranking, and reinforcement learning. Additionally, you will handle multimodal datasets and develop reasoning pipelines across text, image, and audio modalities. Your responsibilities will also include validating and optimizing prompts for large language model performance and translating research into scalable, production-level implementations. Collaboration with cross-functional teams such as Engineering, Product, and Research is essential to ensure the success of our projects. To qualify for this position, you should have a minimum of 4 years of hands-on experience in Data Science or Machine Learning roles. Proficiency in Python, PyTorch/TensorFlow, scikit-learn, and ML lifecycle tools is required. You should also demonstrate expertise in at least one of the following areas: trajectory modeling, preference ranking, or multimodal systems. Experience with LLM prompt engineering, complex reasoning algorithms, graph-based methods, and causal inference is highly beneficial. Strong problem-solving, analytical thinking, and communication skills are essential for success in this role. Preferred skills for this position include familiarity with tools like LangChain, Hugging Face, or OpenAI APIs, exposure to RLHF (Reinforcement Learning from Human Feedback) or prompt-tuning, and experience with deploying ML models in production environments using technologies such as Docker and MLflow. By joining Objectways, you will have the opportunity to work on high-impact, next-generation AI challenges, collaborate with top talent from various domains, and enjoy a competitive salary with benefits and a learning budget.,

As a Data Scientist specializing in Natural Language Processing (NLP) and Large Language Models (LLMs), you will play a crucial role in designing, fine-tuning, and deploying cutting-edge open-source and API-based LLMs to address real-world challenges. Your primary focus will be on creating robust GenAI pipelines, innovative internal tools, and engaging client-facing applications. You will have the exciting opportunity to work at the forefront of AI technology, contributing to the advancement of intelligent systems through the utilization of Retrieval-Augmented Generation (RAG) frameworks, vector databases, and real-time inference APIs. Your responsibilities will include fine-tuning and optimizing open-source LLMs for specific business domains, constructing and managing RAG pipelines using tools like LangChain, FAISS, and ChromaDB, as well as developing LLM-powered APIs for diverse applications such as chat, Q&A, summarization, and classification. Additionally, you will be tasked with designing effective prompt templates and implementing chaining strategies to enhance LLM performance across various contexts. To excel in this role, you should possess a strong foundation in NLP fundamentals and deep learning techniques for text data, hands-on experience with LLM frameworks like Hugging Face Transformers or OpenAI APIs, and familiarity with tools such as LangChain, FAISS, and ChromaDB. Proficiency in developing REST APIs to support ML models, expertise in Python programming with knowledge of libraries like PyTorch or TensorFlow, and a solid grasp of data structures, embedding techniques, and vector search systems are also essential. Preferred qualifications include prior experience in LLM fine-tuning and evaluation, exposure to cloud-based ML deployment (AWS, GCP, Azure), and a background in information retrieval, question answering, or semantic search. If you are passionate about generative AI and eager to contribute to the latest developments in NLP and LLMs, we are excited to connect with you.,

Amplework Software is a full-stack development agency that specializes in providing end-to-end software development solutions to clients globally. The company is dedicated to delivering high-quality products that meet business requirements by utilizing advanced technologies. Their expertise includes custom software development, mobile applications, AI-driven solutions, and enterprise applications. By joining Amplework Software, you will become part of an innovative team that is focused on driving digital transformation through technology. As an Mid-Level Python and AI Engineer at Amplework Software, your responsibilities will include assisting in building and training machine learning models using frameworks like TensorFlow, PyTorch, and Scikit-Learn. You will have the opportunity to experiment with pre-trained AI models for NLP, Computer Vision, and Predictive Analytics. Additionally, you will work with both structured and unstructured data, conduct preprocessing, and engage in feature engineering. Collaboration with data scientists and software engineers to integrate AI solutions into real-world applications is a key aspect of this role. Continuously learning, experimenting, and optimizing models to enhance performance and efficiency is also part of the job. Ideal candidates for this position should possess a strong foundation in Python, basic machine learning concepts, and a willingness to learn. Required qualifications include a Bachelor's degree in Computer Science, Engineering, AI, or a related field, proficiency in Python with experience in writing optimized and clean code, strong problem-solving skills, and an understanding of machine learning concepts such as linear regression, classification, decision trees, and feature engineering. Experience with data processing libraries like Pandas, NumPy, and Matplotlib, as well as basic knowledge of AI models and neural networks using frameworks such as Scikit-Learn, TensorFlow, or PyTorch are also required. Preferred qualifications for this role include experience with Natural Language Processing (NLP) using transformers, BERT, GPT, or OpenAI APIs, basic understanding of AI model deployment using Flask, FastAPI, or TensorFlow Serving, experience with SQL or NoSQL databases for querying datasets in AI applications, and participation in AI-related competitions, hackathons, or open-source projects. In addition to technical skills, soft skills and work ethics are also important for this role. Candidates should have a strong analytical and problem-solving mindset, the ability to work collaboratively in a team, communicate technical concepts effectively, eagerness to learn and apply new AI techniques, and excellent English communication skills, both written and verbal. Candidates who prefer strictly rule-based programming without flexibility for AI experimentation may not be suitable for this position due to the requirement for strong problem-solving skills and quick learning abilities. A face-to-face interview will be conducted, and applicants should only apply if they are able to attend the interview at the office. Joining the Amplework Software team offers the opportunity to be part of a passionate and collaborative team, work on cutting-edge projects, make a real impact, enjoy competitive benefits, and experience a great working environment.,

My profile - linkedin.com/in/yashsharma1608 Location: Noida, Sector 9 Working Days: 5 / 6 days a week (depending on interview) Joining: Immediate Joiners Preferred Python Developer (AI Platforms Trading, Indicators & Automation) Minimum 2 Years About the Role We're looking for a talented Python Developer to help drive the backend and AI logic behind high-growth platforms: This is a versatile role where youll work on data ingestion, AI workflows, API integration, signal generation, backend services, and task automation. Key Responsibilities Develop and maintain Python-based APIs and backend services using FastAPI or Flask Build and manage AI pipelines (e.g. signal generation, retraining, inference logging) Integrate with trading APIs, charting libraries, and third-party tools Work on Pine Script data handling, indicator signal syncing, and confidence scoring logic Implement automation tools for social content generation, scheduling, and analytics Collaborate with frontend, data, and AI teams for end-to-end feature delivery Required Skills 2+ years of hands-on Python development Experience with FastAPI, Flask, or similar frameworks Strong understanding of REST APIs and async workflows Familiarity with task queues (Celery/Redis), logging, and cron automation Exposure to NumPy, pandas, or similar data processing tools Experience integrating with third-party APIs (e.g. TradingView, Twitter, Telegram) Bonus Skills Basic experience with Pine Script or Trading Indicators Familiarity with ML tools (e.g. scikit-learn, HuggingFace, OpenAI APIs) Knowledge of financial data formats, charting, and signal evaluation Hands-on with strategy backtesting, WebSocket feeds, or real-time alerts

We're hiring a passionate Data Scientist / GenAI Engineer to join our AI-first team working on LLMs, RAG pipelines, NLP features, and GenAI use cases like chatbots, recommendation engines, and smart automation.

Here is how, through this exciting role, YOU will contribute to BMC's and your own success: Assist in developing AI-powered QA automation tools using LLMs Collaborate with QA engineers to understand test requirements and translate them into automated scripts Use LLMs to generate test cases, validation scripts, and test data automatically Maintain, debug, and optimize automated test scripts and frameworks Integrate LLM-based solutions into existing CI/CD pipelines and QA workflows Document automation processes and assist with training teams on new AI-driven QA tools Continuously research and apply advancements in LLMs and AI for QA improvements To ensure youre set up for success, you will bring the following skillset & experience: You have 3-5 years for software development experience You have experince of basic programming skills in Python, JavaScript, or relevant languages for automation You have understanding of software testing concepts and QA automation tools (e.g., Selenium, Cypress, JUnit) You have some experience in AI, NLP, or machine learning concepts You are familiarity with version control systems such as Git You have strong problem-solving skills and ability to learn quickly in a dynamic environment Whilst these are nice to have, our team can help you develop in the following skills: Experience with AI/ML frameworks like PyTorch or TensorFlow Familiarity with Large Language Models such as GPT, BERT, or OpenAI APIs Knowledge of continuous integration tools (Jenkins, GitHub Actions) Exposure to writing or maintaining automated test frameworks Understanding of cloud environments for deploying automation solutions

Job Title: Staff Engineer Gen-AI Experience: 8.0 Year To 10.0 Year CTC Salary: 50.00 LPA To 65.00 LPA Location: Bengaluru/Bangalore Job Description Build Gen-AI native products: Architect, build, and ship platforms powered by LLMs, agents, and predictive AI. Stay hands-on: Design systems, write code, debug, and drive product excellence. Lead with depth: Mentor a high-caliber team of full stack engineers. Speed to market: Rapidly ship and iterate on MVPs to maximize learning and feedback. Own the full stack: From backend data pipelines to intuitive UIsfrom Airflow to React from BigQuery to embeddings. Scale what works: Ensure scalability, security, and performance in multi-tenant, cloud-native environments (GCP). Collaborate deeply: Work closely with product, growth, and leadership to align tech with business priorities. What You Bring 8+ years of experience building and scaling full-stack, data-driven products Proficiency in backend (Node.js, Python) and frontend (React), with solid GCP experience Strong grasp of data pipelines, analytics, and real-time data processing Familiarity with Gen-AI frameworks (LangChain, LlamaIndex, OpenAI APIs, vector databases) Proven architectural leadership and technical ownership Product mindset with a bias for execution and iteration Our Tech Stack Cloud: Google Cloud Platform Backend: Node.js, Python, Airflow Data: BigQuery, Cloud SQL AI/ML: TensorFlow, OpenAI APIs, custom agents Frontend: React.js Interested professional can share Resume at harshita.g@recex.co Thanks & Regards Harshita Recex

ABOUT THE ROLE Role Description: We are seeking an accomplished and visionary Data Scientist/ GenAI developer to join Amgens Enterprise Data Management team. As part of MDM team, you will be responsible for design ing , develop ing , and deploy ing Generative AI and ML models to power data-driven decisions across business domains. This role is ideal for an AI practitioner who thrives in a collaborative environment and brings a strategic mindset to applying advanced AI techniques to solve real-world problems. To succeed in this role, the candidate must have strong AI/ML, Data Science , GenAI experience along with MDM knowledge, hence the candidates having only MDM experience are not eligible for this role. Candidate must have AI/ML, data science and GenAI experience on technologies like ( PySpark / PyTorch , TensorFlow, LLM , Autogen , Hugging FaceVectorDB , Embeddings, RAGs etc ), along with knowledge of MDM (Master Data Management) Roles & Responsibilities: Develop enterprise-level GenAI applications using LLM frameworks such as Langchain, Autogen, and Hugging Face. Design and develop intelligent pipelines using PySpark, TensorFlow, and PyTorch within Databricks and AWS environments. Implement embedding models andmanage VectorStores for retrieval-augmented generation (RAG) solutions. Integrate and leverage MDM platforms like Informatica and Reltio to supply high-quality structured data to ML systems. Utilize SQL and Python for data engineering, data wrangling, and pipeline automation. Build scalable APIs and services to serve GenAI models in production. Lead cross-functional collaboration with data scientists, engineers, and product teams to scope, design, and deploy AI-powered systems. Ensure model governance, version control, and auditability aligned with regulatory and compliance expectations. Basic Qualifications and Experience: Masters degree with 4 - 6 years of experience in Business, Engineering, IT or related field OR Bachelors degree with 6 - 9 years of experience in Business, Engineering, IT or related field OR Diploma with 10 - 12 years of experience in Business, Engineering, IT or related field Functional Skills: Must-Have Skills: 6+ years of experience working in AI/ML or Data Science roles, including designing and implementing GenAI solutions. Extensive hands-on experience with LLM frameworks and tools such as Langchain, Autogen, Hugging Face, OpenAI APIs, and embedding models. Strong programming background with Python, PySpark, and experience in building scalable solutions using TensorFlow, PyTorch, and SK-Learn. Proven track record of building and deploying AI/ML applications in cloud environments such as AWS. Expertise in developing APIs, automation pipelines, and serving GenAI models using frameworks like Django, FastAPI, and DataBricks. Solid experience integrating and managing MDM tools (Informatica/Reltio) and applying data governance best practices. Guide the team on development activities and lead the solution discussions Must have core technical capabilities in GenAI, Data Science space Good-to-Have Skills: Prior experience in Data Modeling, ETL development, and data profiling to support AI/ML workflows. Working knowledge of Life Sciences or Pharma industry standards and regulatory considerations. Proficiency in tools like JIRA and Confluence for Agile delivery and project collaboration. Familiarity with MongoDB, VectorStores, and modern architecture principles for scalable GenAI applications. Professional Certifications : Any ETL certification (e.g. Informatica) Any Data Analysis certification (SQL) Any cloud certification (AWS or AZURE) Data Science and ML Certification Soft Skills: Strong analytical abilities to assess and improve master data processes and solutions. Excellent verbal and written communication skills, with the ability to convey complex data concepts clearly to technical and non-technical stakeholders. Effective problem-solving skills to address data-related issues and implement scalable solutions. Ability to work effectively with global, virtual teams We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Job Description Role *AI Architect Desired Experience Range 12 to 15 years Location of Requirement Pan India- Desired Skills -Technical/Behavioral Must-Have AI/ML Expertise: Strong proficiency in Python, TensorFlow, PyTorch, Scikit-learn, OpenAI APIs, LangChain. Cloud & DevOps: Experience with AWS SageMaker, Azure ML, Google Vertex AI, Docker, Kubernetes, CI/CD. Big Data & Databases: Expertise in Hadoop, Spark, Kafka, SQL, NoSQL, Snowflake, Delta Lake. MLOps & AI Deployment: Hands-on experience with MLflow, Kubeflow, Airflow, FastAPI, Flask, Streamlit. AI Security & Compliance: Deep understanding of model interpretability, AI ethics, adversarial attacks, governance. Good-to-Have Experience with Generative AI & LLMs (GPT, LLaMA, Stable Diffusion, DALLE, etc.). Knowledge of Edge AI & AI-powered IoT solutions. Experience with AutoML tools like Google AutoML, H2O.ai, DataRobot. Familiarity with quantization, pruning, and optimization techniques for AI model efficiency. Hands-on experience with vector databases (FAISS, Pinecone, Weaviate) and Retrieval-Augmented Generation (RAG) architectures. Knowledge of Reinforcement Learning (RL), Bayesian Methods, and Time-Series Forecasting. Experience with Graph Neural Networks (GNNs) and AI in cybersecurity. Exposure to Blockchain & AI integration for secure and decentralized AI applications. Familiarity with natural language processing (NLP) frameworks like Hugging Face Transformers Responsibility of / Expectations from the Role AI Strategy & Architecture Development Define and implement an enterprise AI architecture that aligns with business goals and IT strategies. Develop AI roadmaps, best practices, and governance frameworks to ensure scalability, security, and efficiency. Evaluate, recommend, and integrate cutting-edge AI/ML frameworks, tools, and platforms (AWS, Azure, GCP). Establish best practices for MLOps, AI governance, and ethical AI practices. AI Model Development & Deployment Lead the design, development, and optimization of machine learning, deep learning, and generative AI solutions. Oversee data preprocessing, feature engineering, and model optimization to ensure accuracy and efficiency. Implement MLOps pipelines for model training, deployment, monitoring, and continuous improvement. Work with software engineers to integrate AI solutions into production environments seamlessly. Data Engineering & AI Infrastructure Collaborate with data engineering teams to design robust data pipelines, warehouses, and lakes for AI consumption. Optimize real-time and batch data processing architectures for AI model performance. Ensure AI infrastructure is scalable, cost-effective, and cloud-native where applicable. AI Governance, Security & Compliance Establish AI governance frameworks to ensure models are explainable, fair, and aligned with ethical standards. Ensure compliance with global data privacy laws (GDPR, HIPAA) and AI risk management frameworks. Monitor AI models for bias, drift, and performance degradation and implement proactive mitigation strategies. Leadership & Collaboration Act as a strategic advisor to executives and stakeholders on AI adoption and innovation. Provide technical leadership and mentorship to AI engineers, data scientists, and cross-functional teams. Conduct knowledge-sharing sessions, drive AI training initiatives, and foster a culture of AI excellence.

Job Description Role *AI Architect Desired Experience Range 12 to 15 years Location of Requirement Pan India- Desired Skills -Technical/Behavioral Must-Have AI/ML Expertise: Strong proficiency in Python, TensorFlow, PyTorch, Scikit-learn, OpenAI APIs, LangChain. Cloud & DevOps: Experience with AWS SageMaker, Azure ML, Google Vertex AI, Docker, Kubernetes, CI/CD. Big Data & Databases: Expertise in Hadoop, Spark, Kafka, SQL, NoSQL, Snowflake, Delta Lake. MLOps & AI Deployment: Hands-on experience with MLflow, Kubeflow, Airflow, FastAPI, Flask, Streamlit. AI Security & Compliance: Deep understanding of model interpretability, AI ethics, adversarial attacks, governance. Good-to-Have Experience with Generative AI & LLMs (GPT, LLaMA, Stable Diffusion, DALLE, etc.). Knowledge of Edge AI & AI-powered IoT solutions. Experience with AutoML tools like Google AutoML, H2O.ai, DataRobot. Familiarity with quantization, pruning, and optimization techniques for AI model efficiency. Hands-on experience with vector databases (FAISS, Pinecone, Weaviate) and Retrieval-Augmented Generation (RAG) architectures. Knowledge of Reinforcement Learning (RL), Bayesian Methods, and Time-Series Forecasting. Experience with Graph Neural Networks (GNNs) and AI in cybersecurity. Exposure to Blockchain & AI integration for secure and decentralized AI applications. Familiarity with natural language processing (NLP) frameworks like Hugging Face Transformers Responsibility of / Expectations from the Role AI Strategy & Architecture Development Define and implement an enterprise AI architecture that aligns with business goals and IT strategies. Develop AI roadmaps, best practices, and governance frameworks to ensure scalability, security, and efficiency. Evaluate, recommend, and integrate cutting-edge AI/ML frameworks, tools, and platforms (AWS, Azure, GCP). Establish best practices for MLOps, AI governance, and ethical AI practices. AI Model Development & Deployment Lead the design, development, and optimization of machine learning, deep learning, and generative AI solutions. Oversee data preprocessing, feature engineering, and model optimization to ensure accuracy and efficiency. Implement MLOps pipelines for model training, deployment, monitoring, and continuous improvement. Work with software engineers to integrate AI solutions into production environments seamlessly. Data Engineering & AI Infrastructure Collaborate with data engineering teams to design robust data pipelines, warehouses, and lakes for AI consumption. Optimize real-time and batch data processing architectures for AI model performance. Ensure AI infrastructure is scalable, cost-effective, and cloud-native where applicable. AI Governance, Security & Compliance Establish AI governance frameworks to ensure models are explainable, fair, and aligned with ethical standards. Ensure compliance with global data privacy laws (GDPR, HIPAA) and AI risk management frameworks. Monitor AI models for bias, drift, and performance degradation and implement proactive mitigation strategies. Leadership & Collaboration Act as a strategic advisor to executives and stakeholders on AI adoption and innovation. Provide technical leadership and mentorship to AI engineers, data scientists, and cross-functional teams. Conduct knowledge-sharing sessions, drive AI training initiatives, and foster a culture of AI excellence.

Job Description Role *AI Architect Desired Experience Range 12 to 15 years Location of Requirement Pan India- Desired Skills -Technical/Behavioral Must-Have AI/ML Expertise: Strong proficiency in Python, TensorFlow, PyTorch, Scikit-learn, OpenAI APIs, LangChain. Cloud & DevOps: Experience with AWS SageMaker, Azure ML, Google Vertex AI, Docker, Kubernetes, CI/CD. Big Data & Databases: Expertise in Hadoop, Spark, Kafka, SQL, NoSQL, Snowflake, Delta Lake. MLOps & AI Deployment: Hands-on experience with MLflow, Kubeflow, Airflow, FastAPI, Flask, Streamlit. AI Security & Compliance: Deep understanding of model interpretability, AI ethics, adversarial attacks, governance. Good-to-Have Experience with Generative AI & LLMs (GPT, LLaMA, Stable Diffusion, DALLE, etc.). Knowledge of Edge AI & AI-powered IoT solutions. Experience with AutoML tools like Google AutoML, H2O.ai, DataRobot. Familiarity with quantization, pruning, and optimization techniques for AI model efficiency. Hands-on experience with vector databases (FAISS, Pinecone, Weaviate) and Retrieval-Augmented Generation (RAG) architectures. Knowledge of Reinforcement Learning (RL), Bayesian Methods, and Time-Series Forecasting. Experience with Graph Neural Networks (GNNs) and AI in cybersecurity. Exposure to Blockchain & AI integration for secure and decentralized AI applications. Familiarity with natural language processing (NLP) frameworks like Hugging Face Transformers Responsibility of / Expectations from the Role AI Strategy & Architecture Development Define and implement an enterprise AI architecture that aligns with business goals and IT strategies. Develop AI roadmaps, best practices, and governance frameworks to ensure scalability, security, and efficiency. Evaluate, recommend, and integrate cutting-edge AI/ML frameworks, tools, and platforms (AWS, Azure, GCP). Establish best practices for MLOps, AI governance, and ethical AI practices. AI Model Development & Deployment Lead the design, development, and optimization of machine learning, deep learning, and generative AI solutions. Oversee data preprocessing, feature engineering, and model optimization to ensure accuracy and efficiency. Implement MLOps pipelines for model training, deployment, monitoring, and continuous improvement. Work with software engineers to integrate AI solutions into production environments seamlessly. Data Engineering & AI Infrastructure Collaborate with data engineering teams to design robust data pipelines, warehouses, and lakes for AI consumption. Optimize real-time and batch data processing architectures for AI model performance. Ensure AI infrastructure is scalable, cost-effective, and cloud-native where applicable. AI Governance, Security & Compliance Establish AI governance frameworks to ensure models are explainable, fair, and aligned with ethical standards. Ensure compliance with global data privacy laws (GDPR, HIPAA) and AI risk management frameworks. Monitor AI models for bias, drift, and performance degradation and implement proactive mitigation strategies. Leadership & Collaboration Act as a strategic advisor to executives and stakeholders on AI adoption and innovation. Provide technical leadership and mentorship to AI engineers, data scientists, and cross-functional teams. Conduct knowledge-sharing sessions, drive AI training initiatives, and foster a culture of AI excellence.

My profile - linkedin.com/in/yashsharma1608 Location: Noida, Sector 9 Working Days: 5 / 6 days a week Joining: Immediate Joiners Preferred Python Developer (AI Platforms Trading, Indicators & Automation) Minimum 2 Years About the Role We're looking for a talented Python Developer to help drive the backend and AI logic behind high-growth platforms: This is a versatile role where you’ll work on data ingestion, AI workflows, API integration, signal generation, backend services, and task automation. Key Responsibilities Develop and maintain Python-based APIs and backend services using FastAPI or Flask Build and manage AI pipelines (e.g. signal generation, retraining, inference logging) Integrate with trading APIs, charting libraries, and third-party tools Work on Pine Script data handling, indicator signal syncing, and confidence scoring logic Implement automation tools for social content generation, scheduling, and analytics Collaborate with frontend, data, and AI teams for end-to-end feature delivery Required Skills 2+ years of hands-on Python development Experience with FastAPI, Flask, or similar frameworks Strong understanding of REST APIs and async workflows Familiarity with task queues (Celery/Redis), logging, and cron automation Exposure to NumPy, pandas, or similar data processing tools Experience integrating with third-party APIs (e.g. TradingView, Twitter, Telegram) Bonus Skills Basic experience with Pine Script or Trading Indicators Familiarity with ML tools (e.g. scikit-learn, HuggingFace, OpenAI APIs) Knowledge of financial data formats, charting, and signal evaluation Hands-on with strategy backtesting, WebSocket feeds, or real-time alerts

Gen AI Developer with 2 to 7 years of hands-on experience in to architect and deliver cutting-edge AI solutions using Large Language Models (LLMs), diffusion models, and other generative frameworks.

We are seeking a passionate and skilled Agentic AI Developer with 2 to 5 years of experience in developing intelligent, autonomous systems using modern AI/ML technologies. In this role, you will design and deploy AI agents that demonstrate reasoning, adaptability, and goal-directed behaviorinteracting proactively with tools, APIs, and digital environments. Key Responsibilities Design, build, and deploy agentic AI systems capable of autonomous, goal-oriented decision-making. Develop AI agents using LLMs, reinforcement learning, memory modules, and multi-agent system architectures. Integrate AI models with external tools, APIs, databases, and software systems to facilitate real-world interactions. Collaborate with cross-functional teams including product managers and data scientists to convert business requirements into intelligent AI solutions. Implement memory and feedback mechanisms to create adaptive, context-aware agent behavior. Optimize performance, scalability, and reliability of AI systems in production environments. Required Skills & Qualifications 2 - 5 years of hands-on experience in AI/ML development and deployment. Proficiency in Python and relevant AI/ML libraries (e.g., LangChain, Hugging Face Transformers, TensorFlow, PyTorch, OpenAI APIs). Strong understanding of agentic AI concepts, including autonomous agents, memory, planning, and decision-making. Familiarity with LLM agent frameworks such as LangChain, AutoGPT, CrewAI, or OpenAgents. Experience with RESTful APIs, microservices architecture, and system integrations. Excellent problem-solving and analytical skills with the ability to think independently. Education Bachelors or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related discipline. Preferred (Good to Have) Experience in fintech or enterprise-grade AI solutions. Familiarity with cloud platforms such as AWS, GCP, or Azure. Knowledge of agent simulation environments or multi-agent reinforcement learning (MARL).