15 Datascience Jobs

Zycus is looking for applicants with a strong background in Analytics and Data mining (Web, Social and Big data), Machine Learning, Pattern Recognition, Natural Language Processing, Computational Linguistics, Statistical Modelling, Inferencing, Information Retrieval, Large Scale Distributed Systems, Cloud Computing, Econometrics, Quantitative Marketing, Applied Game Theory, Mechanism Design, Operations Research, Optimization, Human Computer Interaction and Information Visualization. Applicants with a background in other quantitative areas are also encouraged to apply. We are looking for someone who can create and implement AI solutions. If you have built a product like IBM WATSON in the past and not just used WATSON to build applications, this could be the perfect role for you. All successful candidates are expected to dive deep into problem areas of Zycus interest and invent technology solutions to not only advance the current products, but also to generate new product options that can strategically advantage the organization. Role & responsibilities Act as a technical thought leader in collaboration with the analytics leadership team, helping to set the strategy and standards for Machine Learning and advanced analytics Work with senior leaders from all functions to explore opportunities for using advance analytics Provide technical leadership, coaching, and mentoring to talented data scientists and analytics professionals Guide data scientists in the use of advanced statistical, machine learning, and artificial intelligence methodologies Guide the work of other Machine learning team members to provide support and assistance, while also ensuring quality Preferred candidate profile Experience in predictive modelling and predictive software development Skilled at Java, C++, Perl/Python (or similar scripting languages) Experience in using R, Matlab, or any other statistical software Experience in mentoring junior team members, and guiding them on machine learning and data modelling applications Strong communication and data presentation skills Classification (svm, decision tree, random forest, neural network) Regression (linear, polynomial, logistic, etc) Classical Optimization(gradient descent, newton raphson, etc) Graph theory (network analytics) Heuristic Optimization (genetic algorithm, swarm theory) Deep learning (lstm, convolutional nn, recurrent nn) Perks and benefits Five Reasons Why You Should Join Zycus Cloud Product Company : We are a Cloud SaaS Company and our products are created by using the latest technologies like ML and AI. Our UI is in Angular JS and we are developing our mobile apps using React. A Market Leader : Zycus is recognized by Gartner (world's leading market research analyst) as a Leader in Procurement Software Suites. Move between Roles: We believe that change leads to growth and therefore we allow our employees to shift careers and move to different roles and functions within the organization Get a Global Exposure: You get to work and deal with our global customers. Create an Impact: Zycus gives you the environment to create an impact on the product and transform your ideas into reality. Even our junior engineers get the opportunity to work on different product features.

Experience: 10 Years to 17 Years Location : Chennai Siruseri / Pune - Hinjewadi Phase III Role Description: Person will be responsible for leading and managing AI projects, overseeing the development and implementation of AI strategies, and driving innovation in AI technologies. They will collaborate with cross-functional teams to identify business opportunities for AI and ensure successful project execution. He will also stay up-to-date with the latest advancements in AI and provide thought leadership in the field. Should hold strong experience in applying regular data science/AI/ML to solving real world business problems with evolving technologies. Should have strong experience in GTM. Qualifications: Must have spent 10+ years in the Data Science, AI, and Analytics industry solving business problems for customers or for organizations. Strong analytical and problem-solving abilities, with consultative approach to client engagements Must have experience leading teams of Data Scientists, data analysts, NLP engineers etc. Knowledge and experience working in any of the cloud tech-stack, and Data platforms like Snowflake or Databricks, Data mining, Data Science, and Analytics skills. Experience in Machine Learning, NLP, Deep learning etc. techniques. Should hold strong experience in applying regular data science/AI/ML to solving real world business problems with evolving technologies. Knowledge/ experience of Gen AI applications Leadership and project management skills Excellent communication and interpersonal skills Experience in the Analytics/ Data Science/ IT services industry is a plus Master's degree in Computer Science, Data Science, or related field preferred

Required Data Science Engineer for our client Location - Hyderabad Ping your details on whatsapp to 7093357755 we will get back to you. Regards Ram 7093357755

Requirements 6+ years(6 year) of professional software engineering mostly focused on the following: Developing ETL pipelines involving big data. Developing data processing\analytics applications primarily using PySpark. Experience of developing applications on cloud(AWS) mostly using services related to storage, compute, ETL, DWH, Analytics and streaming. Clear understanding and ability to implement distributed storage, processing and scalable applications. Experience of working with SQL and NoSQL database. Ability to write and analyze SQL, HQL and other query languages for NoSQL databases. Proficiency is writing disitributed & scalable data processing code using PySpark, Python and related libraries. Data Engineer AEP Comptency Experience of developing applications that consume the services exposed as ReST APIs. Special Consideration given for Experience of working with Container-orchestration systems like Kubernetes. Experience of working with any enterprise grade ETL tools. Experience & knowledge with Adobe Experience Cloud solutions. Experience & knowledge with Web Analytics or Digital Marketing. Experience & knowledge with Google Cloud platforms. Experience & knowledge with Data Science, ML/AI, R or Jupyter.

Required Data science engineer Exp - 5-10 years Location - Hyderabad, Bangalore Whatsapp your details to this number -7093357755 - age, qualification, experience, preferred location. We will revert to you. Regards HR 7093357755

About the Company : Headquartered in California, U.S.A., GSPANN provides consulting and IT services to global clients. We help clients transform how they deliver business value by helping them optimize their IT capabilities, practices, and operations with our experience in retail, high-technology, and manufacturing. With five global delivery centers and 1900+ employees, we provide the intimacy of a boutique consultancy with the capabilities of a large IT services firm. Role: Data Scientist Experience : 4 to 6 Yrs Location: Hyd, Pune, Gurgaon Job Summary: We are seeking a highly skilled and experienced Data Scientist with a strong background in machine learning, computer vision, natural language processing (NLP), generative artificial intelligence (AI), and cloud technologies. As a Data Scientist, you will be working for a client and driving the development and implementation of advanced data models and algorithms to extract meaningful insights from complex datasets. You will work closely with cross-functional teams, including engineers, researchers, and product managers, to design and deploy cutting-edge AI solutions that address our business needs. The ideal candidate will have a minimum of 3 years of real hands on experience in machine learning , with a proven track record of successfully delivering projects in computer vision, NLP, generative AI, and at least one cloud platform. Responsibilities: Drive the end-to-end development and deployment of machine learning models, from data collection and preprocessing to model training and evaluation, leveraging cloud-based infrastructure and services. Collaborate with cross-functional teams to understand business requirements and translate them into data science projects that deliver tangible value. Develop and implement advanced algorithms and models for computer vision, NLP, and generative AI, using techniques such as deep learning, reinforcement learning, and natural language understanding, while leveraging cloud-based machine learning platforms. Conduct thorough exploratory data analysis and feature engineering to extract meaningful insights and identify key patterns within complex datasets. Stay up-to-date with the latest advancements in machine learning, computer vision, NLP, generative AI, and cloud technologies, and apply the latest research findings to enhance existing models and algorithms. Evaluate and select appropriate cloud-based tools, frameworks, and services to support data science initiatives, ensuring scalability, reliability, and cost-efficiency. Collaborate with cloud engineering teams to optimize the deployment and management of machine learning models in cloud environments. Communicate complex technical concepts and findings to both technical and non-technical stakeholders through clear and concise presentations and reports. Qualifications: Bachelor's or master's degree in computer science, data science, or a related field. Speciality in Statistics is mandatory, a Ph.D. is a plus. Minimum of 3 years of experience in machine learning, with a focus on computer vision, NLP, generative AI, and cloud technologies. Strong expertise in programming languages such as Python, as well as proficiency in relevant libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Proven experience in developing and implementing machine learning models for computer vision tasks, including object detection, image segmentation, and image classification. Deep understanding of NLP techniques, such as natural language understanding, sentiment analysis, named entity recognition, and text classification. Familiarity with generative AI models, such as generative adversarial networks (GANs) and variational autoencoders (VAEs). Solid knowledge of deep learning architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers. Experience working with large-scale datasets and data preprocessing techniques. Proficiency in data visualization and exploratory data analysis. Strong analytical and problem-solving skills, with the ability to think critically and creatively to solve complex challenges. Experience with at least one cloud platforms such as AWS, Azure, or Google Cloud, including knowledge of cloud-based machine learning services and infrastructure. Excellent communication and interpersonal skills, with the ability to collaborate effectively with both technical and non-technical stakeholders.

About the Company : Headquartered in California, U.S.A., GSPANN provides consulting and IT services to global clients. We help clients transform how they deliver business value by helping them optimize their IT capabilities, practices, and operations with our experience in retail, high-technology, and manufacturing. With five global delivery centers and 1900+ employees, we provide the intimacy of a boutique consultancy with the capabilities of a large IT services firm. Role: Data Scientist Experience : 4 to 6 Yrs Location: Hyd, Pune, Gurgaon Job Summary: We are seeking a highly skilled and experienced Data Scientist with a strong background in machine learning, computer vision, natural language processing (NLP), generative artificial intelligence (AI), and cloud technologies. As a Data Scientist, you will be working for a client and driving the development and implementation of advanced data models and algorithms to extract meaningful insights from complex datasets. You will work closely with cross-functional teams, including engineers, researchers, and product managers, to design and deploy cutting-edge AI solutions that address our business needs. The ideal candidate will have a minimum of 3 years of real hands on experience in machine learning , with a proven track record of successfully delivering projects in computer vision, NLP, generative AI, and at least one cloud platform. Responsibilities: Drive the end-to-end development and deployment of machine learning models, from data collection and preprocessing to model training and evaluation, leveraging cloud-based infrastructure and services. Collaborate with cross-functional teams to understand business requirements and translate them into data science projects that deliver tangible value. Develop and implement advanced algorithms and models for computer vision, NLP, and generative AI, using techniques such as deep learning, reinforcement learning, and natural language understanding, while leveraging cloud-based machine learning platforms. Conduct thorough exploratory data analysis and feature engineering to extract meaningful insights and identify key patterns within complex datasets. Stay up-to-date with the latest advancements in machine learning, computer vision, NLP, generative AI, and cloud technologies, and apply the latest research findings to enhance existing models and algorithms. Evaluate and select appropriate cloud-based tools, frameworks, and services to support data science initiatives, ensuring scalability, reliability, and cost-efficiency. Collaborate with cloud engineering teams to optimize the deployment and management of machine learning models in cloud environments. Communicate complex technical concepts and findings to both technical and non-technical stakeholders through clear and concise presentations and reports. Qualifications: Bachelor's or master's degree in computer science, data science, or a related field. Speciality in Statistics is mandatory, a Ph.D. is a plus. Minimum of 3 years of experience in machine learning, with a focus on computer vision, NLP, generative AI, and cloud technologies. Strong expertise in programming languages such as Python, as well as proficiency in relevant libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Proven experience in developing and implementing machine learning models for computer vision tasks, including object detection, image segmentation, and image classification. Deep understanding of NLP techniques, such as natural language understanding, sentiment analysis, named entity recognition, and text classification. Familiarity with generative AI models, such as generative adversarial networks (GANs) and variational autoencoders (VAEs). Solid knowledge of deep learning architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers. Experience working with large-scale datasets and data preprocessing techniques. Proficiency in data visualization and exploratory data analysis. Strong analytical and problem-solving skills, with the ability to think critically and creatively to solve complex challenges. Experience with at least one cloud platforms such as AWS, Azure, or Google Cloud, including knowledge of cloud-based machine learning services and infrastructure. Excellent communication and interpersonal skills, with the ability to collaborate effectively with both technical and non-technical stakeholders.

About the Company : Headquartered in California, U.S.A., GSPANN provides consulting and IT services to global clients. We help clients transform how they deliver business value by helping them optimize their IT capabilities, practices, and operations with our experience in retail, high-technology, and manufacturing. With five global delivery centers and 1900+ employees, we provide the intimacy of a boutique consultancy with the capabilities of a large IT services firm. Role: GenAI Solution Architect/Lead Experience : 6+ Yrs Location: Pune Job Position (Title) GenAI Solution Architect/Lead Technical Skill Requirements :LLMs, Python, Cloud, Azure AI/Azure ML, Chatbot, MLOps, LLMOps, Data Science Responsibilities We are seeking a highly skilled and experienced Lead Data Scientist with a strong background in machine learning, computer vision, natural language processing (NLP), generative AI, LLM and cloud technologies. As the Lead Data Scientist, you will be responsible for leading our data science team on for the client and driving the design, architecture, development and implementation of Generative AI based applications. You will be responsible for providing solutions by continuously keeping up with the new developments in this space. You will work closely with cross-functional teams, including engineers, researchers, and product managers, to design and deploy cutting-edge GenAI solutions that address our business needs. The ideal candidate will have a minimum of 5 years of real hands on experience in machine learning/LLMs with expert level python coding skills, with a proven track record of successfully delivering projects in computer vision, NLP, generative AI, and at least one cloud platform. Responsibilities: Drive the end-to-end development and deployment of GenAI based applications, instrumenting model tuning and evaluation and managing model drifts leveraging cloud-based infrastructure and services. Collaborate with cross-functional teams to understand business requirements and translate them into data science projects that deliver tangible value. Stay up-to-date with the latest advancements in Chat/voice bot, NLP, generative AI, and cloud technologies, and apply the latest research findings to enhance existing models and algorithms. Evaluate and select appropriate cloud-based tools, frameworks, and services to support data science initiatives, ensuring scalability, reliability, and cost-efficiency. Collaborate with cloud engineering teams to optimize the deployment and management of machine learning models in cloud environments. Communicate complex technical concepts and findings to both technical and non-technical stakeholders through clear and concise presentations and reports. Required Skills : Bachelor's or master's degree in computer science, data science, or a related field. Minimum of 5 years of experience in machine learning, with a focus on chatbot, NLP, generative AI, and cloud technologies. Strong expertise in programming languages such as Python, as well as proficiency in relevant libraries and frameworks. Proven experience in developing and implementing LLM based applications. Deep understanding of GenAI techniques, such as RAGs, Agent base architecture, Prompt Engineering etc. Familiarity with generative AI models, such as generative adversarial networks (GANs) and variational autoencoders (VAEs). Solid knowledge of deep learning architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers is a plus. Experience working with large-scale datasets and data pre-processing techniques. Strong analytical and problem-solving skills, with the ability to think critically and creatively to solve complex challenges. Experience with at least one cloud platforms such as AWS, Azure, or Google Cloud, including knowledge of cloud-based machine learning services and infrastructure. Azure preferable. Excellent communication and interpersonal skills, with the ability to collaborate effectively with both technical and non-technical stakeholders.

About the Company : Headquartered in California, U.S.A., GSPANN provides consulting and IT services to global clients. We help clients transform how they deliver business value by helping them optimize their IT capabilities, practices, and operations with our experience in retail, high-technology, and manufacturing. With five global delivery centers and 1900+ employees, we provide the intimacy of a boutique consultancy with the capabilities of a large IT services firm. Role: GenAI Solution Architect/Lead Experience : 6+ Yrs Location: Pune Job Position (Title) GenAI Solution Architect/Lead Technical Skill Requirements :LLMs, Python, Cloud, Azure AI/Azure ML, Chatbot, MLOps, LLMOps, Data Science Responsibilities We are seeking a highly skilled and experienced Lead Data Scientist with a strong background in machine learning, computer vision, natural language processing (NLP), generative AI, LLM and cloud technologies. As the Lead Data Scientist, you will be responsible for leading our data science team on for the client and driving the design, architecture, development and implementation of Generative AI based applications. You will be responsible for providing solutions by continuously keeping up with the new developments in this space. You will work closely with cross-functional teams, including engineers, researchers, and product managers, to design and deploy cutting-edge GenAI solutions that address our business needs. The ideal candidate will have a minimum of 5 years of real hands on experience in machine learning/LLMs with expert level python coding skills, with a proven track record of successfully delivering projects in computer vision, NLP, generative AI, and at least one cloud platform. Responsibilities: Drive the end-to-end development and deployment of GenAI based applications, instrumenting model tuning and evaluation and managing model drifts leveraging cloud-based infrastructure and services. Collaborate with cross-functional teams to understand business requirements and translate them into data science projects that deliver tangible value. Stay up-to-date with the latest advancements in Chat/voice bot, NLP, generative AI, and cloud technologies, and apply the latest research findings to enhance existing models and algorithms. Evaluate and select appropriate cloud-based tools, frameworks, and services to support data science initiatives, ensuring scalability, reliability, and cost-efficiency. Collaborate with cloud engineering teams to optimize the deployment and management of machine learning models in cloud environments. Communicate complex technical concepts and findings to both technical and non-technical stakeholders through clear and concise presentations and reports. Required Skills : Bachelor's or master's degree in computer science, data science, or a related field. Minimum of 5 years of experience in machine learning, with a focus on chatbot, NLP, generative AI, and cloud technologies. Strong expertise in programming languages such as Python, as well as proficiency in relevant libraries and frameworks. Proven experience in developing and implementing LLM based applications. Deep understanding of GenAI techniques, such as RAGs, Agent base architecture, Prompt Engineering etc. Familiarity with generative AI models, such as generative adversarial networks (GANs) and variational autoencoders (VAEs). Solid knowledge of deep learning architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers is a plus. Experience working with large-scale datasets and data pre-processing techniques. Strong analytical and problem-solving skills, with the ability to think critically and creatively to solve complex challenges. Experience with at least one cloud platforms such as AWS, Azure, or Google Cloud, including knowledge of cloud-based machine learning services and infrastructure. Azure preferable. Excellent communication and interpersonal skills, with the ability to collaborate effectively with both technical and non-technical stakeholders.

About the Company : Headquartered in California, U.S.A., GSPANN provides consulting and IT services to global clients. We help clients transform how they deliver business value by helping them optimize their IT capabilities, practices, and operations with our experience in retail, high-technology, and manufacturing. With five global delivery centers and 1900+ employees, we provide the intimacy of a boutique consultancy with the capabilities of a large IT services firm. Role: Senior AIML Engineer Experience : 6+ Yrs Location: Pune Skillsets- AIML , Gen AI, MLOps, AWS, Python, ML(Machine Learning), Data Science , SQL,AWS Job Summary: We are seeking a highly skilled and experienced Data Scientist with a strong background in machine learning, computer vision, natural language processing (NLP), generative artificial intelligence (AI), and cloud technologies. As a Data Scientist, you will be working for a client and driving the development and implementation of advanced data models and algorithms to extract meaningful insights from complex datasets. You will work closely with cross-functional teams, including engineers, researchers, and product managers, to design and deploy cutting-edge AI solutions that address our business needs. The ideal candidate will have a minimum of 3 years of real hands on experience in machine learning , with a proven track record of successfully delivering projects in computer vision, NLP, generative AI, and at least one cloud platform. The Role: As our Tech Lead in AI/ML, you will play a crucial role in the hands-on development of mentoring peers and delivery of AI products powered by our internal AI models and machine learning pipelines. You'll identify new opportunities for AI solutions throughout the organization, and set the direction and roadmap required to implement MLOPS. You will partner with the team through the creation of AI models, and develop, and deploy LLM-based applications in production, evaluating and improving their performance and accuracy over time. Collaborating closely with Product, Research, and Engineering teams, youll ensure seamless integration of AI technologies into our products, setting new standards for data quality and model performance. Responsibilities: Design, develop, and maintain a AI/ML platform that is accurate, secure, and fast Lead workstreams within a lean and agile environment from requirements gathering to creating a plan of actionable tasks for the team Provide coaching, and mentorship to members of the data team on architecture, software development best practices, and new technologies Establish evaluation criteria for data quality tracking and production ML model tracking Partner with product, research, and engineering to ensure product changes integrate effectively . Required Qualifications: 6+ years in MLOps, ML engineering, MLOps, and data science with 2+ years leading and mentoring agile teams. Proven expertise in deploying essential MLOps components like CI/CD, model registry, and input loading. Skilled in creating and launching diverse models (statistical, LLM, GenAI, GPT 3.5/4.0) from POC to production. Proven ability to manage projects and programs, leading small teams (2-5 members) and directly handling data analysis, modeling, data pipeline setup, and MLOps Skilled in AIML, using platforms like AWS, Amazon Bedrock, and Snowflake, and proficient in Python, SQL, Tableau, and Alteryx 3+ years of experience working with Jupyter Notebooks, Git, GitHub, JIRA, and weights & biases, enhancing collaboration and version control in project development. Significant collaboration with research teams, contributing hands-on research skills that advance project outcomes. Preferred Qualifications: 2+ years of Tech Lead and management experience; taking on role as player coach and providing mentorship. Experience migrating data sets and workflows between legacy data platforms and services. Familiarity with stream processing and event driven architecture Comfortable moving quickly and working in a fast-paced, agile XP, lean environment. Experience in leading offshore and nearshore teams is highly valued.

About the Company : Headquartered in California, U.S.A., GSPANN provides consulting and IT services to global clients. We help clients transform how they deliver business value by helping them optimize their IT capabilities, practices, and operations with our experience in retail, high-technology, and manufacturing. With five global delivery centers and 1900+ employees, we provide the intimacy of a boutique consultancy with the capabilities of a large IT services firm. Role: Senior AIML Engineer Experience : 6+ Yrs Location: Pune Skillsets- AIML , Gen AI, MLOps, AWS, Python, ML(Machine Learning), Data Science , SQL,AWS Job Summary: We are seeking a highly skilled and experienced Data Scientist with a strong background in machine learning, computer vision, natural language processing (NLP), generative artificial intelligence (AI), and cloud technologies. As a Data Scientist, you will be working for a client and driving the development and implementation of advanced data models and algorithms to extract meaningful insights from complex datasets. You will work closely with cross-functional teams, including engineers, researchers, and product managers, to design and deploy cutting-edge AI solutions that address our business needs. The ideal candidate will have a minimum of 3 years of real hands on experience in machine learning , with a proven track record of successfully delivering projects in computer vision, NLP, generative AI, and at least one cloud platform. The Role: As our Tech Lead in AI/ML, you will play a crucial role in the hands-on development of mentoring peers and delivery of AI products powered by our internal AI models and machine learning pipelines. You'll identify new opportunities for AI solutions throughout the organization, and set the direction and roadmap required to implement MLOPS. You will partner with the team through the creation of AI models, and develop, and deploy LLM-based applications in production, evaluating and improving their performance and accuracy over time. Collaborating closely with Product, Research, and Engineering teams, youll ensure seamless integration of AI technologies into our products, setting new standards for data quality and model performance. Responsibilities: Design, develop, and maintain a AI/ML platform that is accurate, secure, and fast Lead workstreams within a lean and agile environment from requirements gathering to creating a plan of actionable tasks for the team Provide coaching, and mentorship to members of the data team on architecture, software development best practices, and new technologies Establish evaluation criteria for data quality tracking and production ML model tracking Partner with product, research, and engineering to ensure product changes integrate effectively . Required Qualifications: 6+ years in MLOps, ML engineering, MLOps, and data science with 2+ years leading and mentoring agile teams. Proven expertise in deploying essential MLOps components like CI/CD, model registry, and input loading. Skilled in creating and launching diverse models (statistical, LLM, GenAI, GPT 3.5/4.0) from POC to production. Proven ability to manage projects and programs, leading small teams (2-5 members) and directly handling data analysis, modeling, data pipeline setup, and MLOps Skilled in AIML, using platforms like AWS, Amazon Bedrock, and Snowflake, and proficient in Python, SQL, Tableau, and Alteryx 3+ years of experience working with Jupyter Notebooks, Git, GitHub, JIRA, and weights & biases, enhancing collaboration and version control in project development. Significant collaboration with research teams, contributing hands-on research skills that advance project outcomes. Preferred Qualifications: 2+ years of Tech Lead and management experience; taking on role as player coach and providing mentorship. Experience migrating data sets and workflows between legacy data platforms and services. Familiarity with stream processing and event driven architecture Comfortable moving quickly and working in a fast-paced, agile XP, lean environment. Experience in leading offshore and nearshore teams is highly valued.

About the Company : Headquartered in California, U.S.A., GSPANN provides consulting and IT services to global clients. We help clients transform how they deliver business value by helping them optimize their IT capabilities, practices, and operations with our experience in retail, high-technology, and manufacturing. With five global delivery centers and 1900+ employees, we provide the intimacy of a boutique consultancy with the capabilities of a large IT services firm. Role: AI Operations (AI Ops) Engineer Experience : 8+ Yrs Location: Pune, Hyderabad, Gurugram Skillsets- Azure, Gen AI, MLOps, Python, ML(Machine Learning), Data Science , SQL Job Summary: AI Operations (AI Ops) Engineer AI Ops Engineer with a strong background in Python, API development, Large Language Models (LLM) concepts, ML Ops, Azure Cloud and AI operations with 8-10 years of experience working on advanced AI/ML systems, cloud infrastructure, and API integrations, with a focus on operationalizing AI models and maintaining robust systems for AI-driven applications. This role requires a combination of technical expertise in cloud computing, machine learning, and software engineering. Collaborate with IT operations and business teams to support business user issues, requests, Production support and deployments; advocate best practices and recommend technical solutions for improvements in usability of application and systems performance Key Responsibilities: Technical Operations: Review, Implement and support enterprise-level AI platforms and services to drive IT operation excellence. Ensuring that new use cases are onboarded smoothly and operationalized Optimization: Analyze business processes to identify areas for automation and work with business stakeholders and IT teams to determine requirements and design software bots to reduce operational toil. AI Ops & Model Deployment: Lead the operationalization and deployment of AI/ML models into production environments, ensuring they are highly available, scalable, and performant. Implement and monitor Continuous Integration (CI) and Continuous Deployment (CD) pipelines. Python Development: Design and develop Python-based solutions for automating and managing the lifecycle of AI/ML models, including data ingestion, model training, and real-time prediction workflows. API Integration: Build and maintain robust APIs for model serving and integration with other systems. Ensure seamless communication between models, data pipelines, and consumer applications. LLM Concepts and Implementation: Apply knowledge of Large Language Models (LLMs) to develop AI-driven applications and services, ensuring models are optimized and performing efficiently in production. ML Ops: Implement and maintain Machine Learning Operations (ML Ops) practices for version control, monitoring, logging, and debugging of AI/ML models in production. Support model retraining, versioning, and A/B testing. Cloud Infrastructure: Leverage Azure Cloud services for hosting and scaling AI applications, ensuring security, compliance, and performance. Implement infrastructure as code (IaC) using tools like Azure DevOps. Collaboration: Work closely with backend engineers, data engineers/developers, infrastructure engineers , operational SMEs and business stakeholders to tackle evolving challenges in the field of AI/ML to ensure AI solutions meet business requirements and performance benchmarks. Monitoring & Optimization: Continuously monitor the performance of deployed AI models and optimize them for efficiency, cost-effectiveness, and accuracy. Implement alerting and logging mechanisms by scripts or through observability solution. Documentation & Best Practices: Document AI Ops processes, Use cases, tools, and workflows. Establish and enforce best practices for managing AI models in production environments. Required Skills & Qualifications:(Python Developer + ML-Engineer + MLOPS+ Azure) Experience: 8-10 years of experience in software development, with a focus on AI/ML operations, cloud infrastructure, and DevOps practices. -Data ScienePython: Advanced proficiency in Python, including experience with AI/ML libraries such as TensorFlow, PyTorch, scikit-learn, and Pandas. MLOPS Engineer APIs: Strong experience in designing, developing, and maintaining RESTful APIs for AI/ML model deployment and integration. ML Ops: In-depth understanding of Machine Learning Operations, including model versioning, monitoring, deployment, and automation of ML workflows. Data Science LLM Concepts: Familiarity with Large Language Models (LLMs), including experience working with transformer-based models such as GPT, BERT, or T5. Data Engineer Azure Cloud: Hands-on experience with Azure Cloud services (Azure ML, Azure DevOps, Azure Functions, etc.) and cloud infrastructure management. DevOps & CI/CD: Proficient in setting up CI/CD pipelines for AI/ML models and using tools like Jenkins, GitLab, or Azure DevOps for automation. DE Data Management & Tools: Experience working with data storage and processing tools like Azure Blob Storage, Azure SQL Database, Kafka, or similar. Version Control: Expertise with Git and version control best practices for collaborative development of AI systems. Problem Solving: Strong analytical and troubleshooting skills, with the ability to identify root causes and optimize AI/ML models and systems. Communication & Collaboration: Excellent communication skills and the ability to work effectively in a cross-functional team environment. Preferred Skills: Cloud Certifications: Azure certifications such as Azure Solutions Architect, Azure AI Engineer, or Azure DevOps Engineer. Security & Compliance: Understanding of security best practices in AI model deployment and experience with secure handling of sensitive data in the cloud. Big Data Tools: Familiarity with big data processing frameworks (e.g., Apache Spark, Hadoop) and integration with AI/ML pipelines. Agile Methodologies: Experience working in Agile teams, with knowledge of Scrum, Kanban, or similar frameworks. Education: A Bachelor's or Masters degree in Computer Science, Engineering, Data Science, or a related field is preferred.

About the Company : Headquartered in California, U.S.A., GSPANN provides consulting and IT services to global clients. We help clients transform how they deliver business value by helping them optimize their IT capabilities, practices, and operations with our experience in retail, high-technology, and manufacturing. With five global delivery centers and 1900+ employees, we provide the intimacy of a boutique consultancy with the capabilities of a large IT services firm. Role: AI Operations (AI Ops) Engineer Experience : 8+ Yrs Location: Pune, Hyderabad, Gurugram Skillsets- Azure, Gen AI, MLOps, Python, ML(Machine Learning), Data Science , SQL Job Summary: AI Operations (AI Ops) Engineer AI Ops Engineer with a strong background in Python, API development, Large Language Models (LLM) concepts, ML Ops, Azure Cloud and AI operations with 8-10 years of experience working on advanced AI/ML systems, cloud infrastructure, and API integrations, with a focus on operationalizing AI models and maintaining robust systems for AI-driven applications. This role requires a combination of technical expertise in cloud computing, machine learning, and software engineering. Collaborate with IT operations and business teams to support business user issues, requests, Production support and deployments; advocate best practices and recommend technical solutions for improvements in usability of application and systems performance Key Responsibilities: Technical Operations: Review, Implement and support enterprise-level AI platforms and services to drive IT operation excellence. Ensuring that new use cases are onboarded smoothly and operationalized Optimization: Analyze business processes to identify areas for automation and work with business stakeholders and IT teams to determine requirements and design software bots to reduce operational toil. AI Ops & Model Deployment: Lead the operationalization and deployment of AI/ML models into production environments, ensuring they are highly available, scalable, and performant. Implement and monitor Continuous Integration (CI) and Continuous Deployment (CD) pipelines. Python Development: Design and develop Python-based solutions for automating and managing the lifecycle of AI/ML models, including data ingestion, model training, and real-time prediction workflows. API Integration: Build and maintain robust APIs for model serving and integration with other systems. Ensure seamless communication between models, data pipelines, and consumer applications. LLM Concepts and Implementation: Apply knowledge of Large Language Models (LLMs) to develop AI-driven applications and services, ensuring models are optimized and performing efficiently in production. ML Ops: Implement and maintain Machine Learning Operations (ML Ops) practices for version control, monitoring, logging, and debugging of AI/ML models in production. Support model retraining, versioning, and A/B testing. Cloud Infrastructure: Leverage Azure Cloud services for hosting and scaling AI applications, ensuring security, compliance, and performance. Implement infrastructure as code (IaC) using tools like Azure DevOps. Collaboration: Work closely with backend engineers, data engineers/developers, infrastructure engineers , operational SMEs and business stakeholders to tackle evolving challenges in the field of AI/ML to ensure AI solutions meet business requirements and performance benchmarks. Monitoring & Optimization: Continuously monitor the performance of deployed AI models and optimize them for efficiency, cost-effectiveness, and accuracy. Implement alerting and logging mechanisms by scripts or through observability solution. Documentation & Best Practices: Document AI Ops processes, Use cases, tools, and workflows. Establish and enforce best practices for managing AI models in production environments. Required Skills & Qualifications:(Python Developer + ML-Engineer + MLOPS+ Azure) Experience: 8-10 years of experience in software development, with a focus on AI/ML operations, cloud infrastructure, and DevOps practices. -Data ScienePython: Advanced proficiency in Python, including experience with AI/ML libraries such as TensorFlow, PyTorch, scikit-learn, and Pandas. MLOPS Engineer APIs: Strong experience in designing, developing, and maintaining RESTful APIs for AI/ML model deployment and integration. ML Ops: In-depth understanding of Machine Learning Operations, including model versioning, monitoring, deployment, and automation of ML workflows. Data Science LLM Concepts: Familiarity with Large Language Models (LLMs), including experience working with transformer-based models such as GPT, BERT, or T5. Data Engineer Azure Cloud: Hands-on experience with Azure Cloud services (Azure ML, Azure DevOps, Azure Functions, etc.) and cloud infrastructure management. DevOps & CI/CD: Proficient in setting up CI/CD pipelines for AI/ML models and using tools like Jenkins, GitLab, or Azure DevOps for automation. DE Data Management & Tools: Experience working with data storage and processing tools like Azure Blob Storage, Azure SQL Database, Kafka, or similar. Version Control: Expertise with Git and version control best practices for collaborative development of AI systems. Problem Solving: Strong analytical and troubleshooting skills, with the ability to identify root causes and optimize AI/ML models and systems. Communication & Collaboration: Excellent communication skills and the ability to work effectively in a cross-functional team environment. Preferred Skills: Cloud Certifications: Azure certifications such as Azure Solutions Architect, Azure AI Engineer, or Azure DevOps Engineer. Security & Compliance: Understanding of security best practices in AI model deployment and experience with secure handling of sensitive data in the cloud. Big Data Tools: Familiarity with big data processing frameworks (e.g., Apache Spark, Hadoop) and integration with AI/ML pipelines. Agile Methodologies: Experience working in Agile teams, with knowledge of Scrum, Kanban, or similar frameworks. Education: A Bachelor's or Masters degree in Computer Science, Engineering, Data Science, or a related field is preferred.

Delivery of sessions on syllabus as per university norms Managing student discipline and learning experience Innovation & Development in pedagogy Create excellent student learning experience Required Candidate profile High Standard Research Publications in ABDC/Scopus/Journals Expertise in organizing conferences/seminars/workshop/FDP's Skills: CSE, IT, Info Security, Cloud, AI, ML, Data Mining, Block Chain etc..

Experience in supply chain, logistics, retail, or e-commerce industry preferred. Job Title: Simulation Expert (Data Scientist / Operations Research) Location: Remote Job Summary Seeking a Simulation Expert (Ph.D. preferred) to design advanced discrete event simulations and develop digital twins for supply chains. The role involves collaborating with cross-functional teams, running "what-if" analyses, and applying optimization techniques to improve decision-making. Key Responsibilities Build and maintain simulation models using Python (SimPy, AnyLogic, etc.). Develop digital twins integrating real-time data. Apply optimization methods for transportation, inventory, and warehouse operations. Analyze data, validate models, and present actionable insights. Collaborate with stakeholders and lead project delivery. Stay updated with the latest tools and mentor junior scientists. Qualifications Ph.D./Masters in a relevant field. 1-3 years of simulation modeling experience. Strong Python, SQL, and data visualization skills. Familiarity with cloud platforms (Azure, AWS) and big data technologies. Excellent communication, problem-solving, and collaboration skills. Experience in supply chain, logistics, or e-commerce is a plus.