66 Torchserve Jobs - Page 3

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.

As a Python Machine Learning & AI Developer at Chicmic Studios, you will be an integral part of our dynamic team, bringing your expertise and experience to develop cutting-edge web applications using Django and Flask frameworks. Your primary responsibilities will include designing and implementing RESTful APIs with Django Rest Framework (DRF), deploying and optimizing applications on AWS services, and integrating AI/ML models into existing systems. You will be expected to create scalable machine learning models using PyTorch, TensorFlow, and scikit-learn, implement transformer architectures like BERT and GPT for NLP and advanced AI use cases, and optimize models through techniques such as hyperparameter tuning, pruning, and quantization. Additionally, you will deploy and manage machine learning models in production environments using tools like TensorFlow Serving, TorchServe, and AWS SageMaker, ensuring the scalability, performance, and reliability of both applications and models. Collaboration with cross-functional teams to analyze requirements, deliver technical solutions, and staying up-to-date with the latest industry trends in AI/ML will also be key aspects of your role. Your ability to write clean, efficient code following best practices, conduct code reviews, and provide constructive feedback to peers will contribute to the success of our projects. To be successful in this role, you should possess a Bachelor's degree in Computer Science, Engineering, or a related field, with at least 3 years of professional experience as a Python Developer. Proficiency in Python, Django, Flask, and AWS services is required, along with expertise in machine learning frameworks, transformer architectures, and database technologies. Familiarity with MLOps practices, front-end technologies, and strong problem-solving skills are also desirable qualities for this position. If you are passionate about leveraging your Python development skills and AI expertise to drive innovation and deliver impactful solutions, we encourage you to apply and be a part of our innovative team at Chicmic Studios.,

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Lead Consultant - ML/CV Ops Engineer ! We are seeking a highly skilled ML CV Ops Engineer to join our AI Engineering team. This role is focused on operationalizing Computer Vision models&mdashensuring they are efficiently trained, deployed, monitored , and retrained across scalable infrastructure or edge environments. The ideal candidate has deep technical knowledge of ML infrastructure, DevOps practices, and hands-on experience with CV pipelines in production. You&rsquoll work closely with data scientists, DevOps, and software engineers to ensure computer vision models are robust, secure, and production-ready always. Key Responsibilities: End-to-End Pipeline Automation: Build and maintain ML pipelines for computer vision tasks (data ingestion, preprocessing, model training, evaluation, inference). Use tools like MLflow , Kubeflow, DVC, and Airflow to automate workflows. Model Deployment & Serving: Package and deploy CV models using Docker and orchestration platforms like Kubernetes. Use model-serving frameworks (TensorFlow Serving, TorchServe , Triton Inference Server) to enable real-time and batch inference. Monitoring & Observability: Set up model monitoring to detect drift, latency spikes, and performance degradation. Integrate custom metrics and dashboards using Prometheus, Grafana, and similar tools. Model Optimization: Convert and optimize models using ONNX, TensorRT , or OpenVINO for performance and edge deployment. Implement quantization, pruning, and benchmarking pipelines. Edge AI Enablement (Optional but Valuable): Deploy models on edge devices (e.g., NVIDIA Jetson, Coral, Raspberry Pi) and manage updates and logs remotely. Collaboration & Support: Partner with Data Scientists to productionize experiments and guide model selection based on deployment constraints. Work with DevOps to integrate ML models into CI/CD pipelines and cloud-native architecture. Qualifications we seek in you! Minimum Qualifications Bachelor&rsquos or Master&rsquos in Computer Science , Engineering, or a related field. Sound experience in ML engineering, with significant work in computer vision and model operations. Strong coding skills in Python and familiarity with scripting for automation. Hands-on experience with PyTorch , TensorFlow, OpenCV, and model lifecycle tools like MLflow , DVC, or SageMaker. Solid understanding of containerization and orchestration (Docker, Kubernetes). Experience with cloud services (AWS/GCP/Azure) for model deployment and storage. Preferred Qualifications: Experience with real-time video analytics or image-based inference systems. Knowledge of MLOps best practices (model registries, lineage, versioning). Familiarity with edge AI deployment and acceleration toolkits (e.g., TensorRT , DeepStream ). Exposure to CI/CD pipelines and modern DevOps tooling (Jenkins, GitLab CI, ArgoCD ). Contributions to open-source ML/CV tooling or experience with labeling workflows (CVAT, Label Studio). Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Principal Consultant - (AI App Ops Lead)! We are looking for a seasoned and hands-on Application Operations Lead to drive the operational excellence of Computer Vision (CV) applications. This individual will lead and mentor a team of ML CV Ops Engineers, ensuring the resilience, scalability, and reliability of AI-powered visual systems deployed in production environments. The ideal candidate will bring a blend of leadership, system operations, ML infrastructure knowledge, and cross-functional collaboration. You will be responsible for orchestrating the delivery, monitoring, and optimization of critical CV models and applications, deployed across cloud and edge environments. Key Responsibilities: Lead and mentor a team of ML CV Ops Engineers to manage the lifecycle of computer vision applications in production. Define and implement operational strategies, workflows, and performance goals for the App Ops team. Foster a DevOps/ MLOps culture of automation, ownership, and continuous improvement. Ensure production CV applications meet high availability, performance, and security standards. Establish SLAs, monitoring policies, and governance frameworks for mission-critical AI systems. Own the incident response process, drive root cause analysis, and coordinate remediation with CV engineering and data science teams. Maintain high observability through monitoring tools (e.g., Prometheus, Grafana, Datadog, AppDynamics). Partner with Data Scientists, MLOps , Cloud Engineers, and Software Developers to ensure smooth model deployments and robust CI/CD pipelines. Act as the technical operations bridge between AI model development and enterprise IT. Champion automation of repetitive support and operational tasks, including model validation, performance regression testing, and retraining triggers. Drive cost and resource optimization for cloud/GPU infrastructure used in CV workloads. Ensure operational practices adhere to audit, security, and regulatory compliance requirements. Maintain operational runbooks, escalation paths, and support documentation for CV systems. Define, Implement, Execute AI App Ops standard work Define KPIs for Support Ops performance and monitor and report on Support Ops KPIs Assist in issue analysis and remediation by developing standard work and investigate, troubleshoot, manage and resolve technical issues Develop code and implement proactive alerting mechanisms Establish and Monitor and act on observability metrics and thresholds Design and Develop proactive alerting mechanisms Create and Implement feedback loop for model observability data Configure and develop scalable pipeline for model integrations Implement observability metrics and thresholds Govern and Support change management processes Assist in knowledge transition and developing training materials Oversee and assist in investigation and resolution of vulnerabilities Transition knowledge from incumbent partner Qualifications we seek in you! Minimum Qualifications Bachelor&rsquos or Master&rsquos degree in Computer Science , Engineering, or a related field. experience in IT Operations, Site Reliability Engineering, or DevOps, with 2+ years in managing ML/AI systems in production. Proven experience in leading technical teams, preferably in ML Ops or platform engineering contexts. Strong understanding of cloud infrastructure (AWS/GCP/Azure), containers (Docker), orchestration (Kubernetes), and CI/CD practices. Experience supporting and optimizing Computer Vision workloads in real-time or batch systems. Familiarity with MLOps platforms and tools (e.g., MLflow , DVC, TensorFlow Serving, TorchServe , Airflow). Preferred Qualifications: Prior experience with model monitoring, drift detection, and retraining automation. Experience working in industries like energy, industrial equipment, manufacturing is a strong plus. Exposure to edge deployment strategies (e.g., NVIDIA Jetson, TensorRT , ONNX optimization). ITIL or SRE certifications are a bonus. Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

You are an experienced Lead Data Scientist with a minimum of 8 years of professional experience, including at least 6 years in a data science role. Your expertise lies in statistical modeling, machine learning, deep learning, and GenAI. Proficiency in Python is a must, along with hands-on experience in optimizing code for performance. You excel in data preprocessing, feature engineering, data visualization, hyperparameter tuning, and have a solid understanding of database concepts, especially while working with large datasets. You have experience deploying and scaling machine learning models in a production environment, along with familiarity with machine learning operations (MLOps) and related tools. Your knowledge extends to Generative AI concepts and LLM finetuning, supported by excellent communication and collaboration skills. Your responsibilities as a Lead Data Scientist include guiding and mentoring a high-performance team on the latest technology landscape, patterns, and design standards. You provide strategic direction and technical leadership for AI initiatives, leading the design and architecture of complex AI systems. Your role involves developing and deploying machine learning/deep learning models to address key business challenges, applying various techniques in statistical modeling, data preprocessing, feature engineering, and more. You are proficient in areas such as computer vision, predictive analytics, natural language processing, time series analysis, and recommendation systems. Furthermore, you design and optimize data pipelines for model training and deployment, utilizing model serving frameworks and APIs for integration with other systems. Your qualifications include a Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Your primary skills encompass Python, Data Science concepts, Pandas, NumPy, Matplotlib, Artificial Intelligence, Statistical Modeling, Machine Learning, Natural Language Processing (NLP), Deep Learning, Model Serving Frameworks, MLOps, Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems, Generative AI, and proficiency in Cloud Computing Platforms. Your secondary skills involve expertise in designing scalable and efficient model architectures, the ability to assess and forecast financial requirements of data science projects, and strong communication skills for conveying technical concepts to stakeholders. As a Lead Data Scientist, you stay updated with the latest advancements in data science and machine learning, particularly in generative AI, to evaluate their potential applications and serve as a primary point of contact for client managers.,