6 Openai Apis Jobs

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