66 Tensorflow Serving Jobs

As a Senior Data Scientist with expertise in Deep Learning and NLP, you will be responsible for researching, designing, and developing core Artificial Intelligence (AI) and Machine Learning (ML) algorithms. Your essential skills will include working experience with various AI frameworks, such as CRFs, BERT/Transformers, and text summarization models. You should have past experience in Entity Detection and Disambiguation, Intent Detection, and deploying machine learning models in a production environment using tools like TensorFlow Serving. Your role will involve collaborating with functional domain experts, implementation teams, and AI backend teams to ensure efficient product development, production release, and development cycles. It is crucial to stay updated with the latest AI developments, including training libraries/frameworks, Reinforcement Learning, and Deep Learning, by reading and researching state-of-the-art papers in NLU problems. You will work with large datasets of support tickets and unstructured data sources, building Deep Learning models in TensorFlow for GPUs and CPUs. Additionally, collaborating with Backend Engineers to deploy your models to production will be part of your responsibilities. Your background should include a Bachelor's degree in B.E/B.Tech, with a strong industry focus on IT/Computers-Software. You must possess a good understanding of Transfer Learning concepts, Question-Answering Framework, and have experience in building production-ready NLP systems. Familiarity with Distributed systems like Docker, Kubernetes, and Azure, as well as working knowledge of Linux OS, will be beneficial for this role. If you have the passion and skills to work on cutting-edge AI technologies, this Senior Data Scientist position offers a challenging opportunity to contribute to the development of innovative NLP systems in a dynamic environment.,

- Proficiency in LLM systems, prompt fine-tuning - experience with infrastructure management, model deployment, and optimization. - Understanding of cloud architecture, performance and scalability. - Experience with machine learning frameworks Health insurance Provident fund

Job Title: Python Developer (38 Years Experience) Location: Chennai Job Type: Full-Time Work Mode: Office (5 Days) Experience Required: 3 to 8 Years Job Description Ability to perform data transformations using Python, pandas, numpy, polars. Ability to query data from SQL and NoSQL databases. For SQL: Given a database schema should be able to create a query to extract desired data. For NoSQL: Experience performing hierarchical queries in REST or experience with GraphQL. Database operation (indexing etc), cache (redis etc), data management, handle missing data etc. Data visualization in Python (Plotly, Bokeh, matplotlib etc.) Some experience with distributed programming using Spark or Dask or similar toolkits that can take sequential code and run it across multiple processes. Familiar with machine learning, experience with deep learning model analysis, popular architectures, augmentations, fine tune, boosting, dimension reduction etc. Basic knowledge of computer vision and image processing, understand concept of feature extraction, object detection and classification, segmentation, denoise, super resolution etc. Familiar with python / tensorflow / pytorch / openCV etc. Good software skill, knows concept and object-oriented design, and basic software system design Experience of organize and aggregate large datasets Good data analysis and analytic skill

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.