24 Job openings found

Job Description We are looking for a Senior Machine Learning Engineer who can take ownership of designing, developing, and deploying Computer Vision solutions in production environments. Responsibilities :As a Senior ML Engineer, you will lead the design, development, and deployment of advanced computer vision systems that power AI automation across ...

About the Role : We are looking for a hands-on Full Stack Data Scientist who can independently manage the  entire machine learning lifecycle—from data wrangling to deployment—without relying on a  dedicated data engineering team. This role is ideal for someone who thrives in a fast-paced, self- directed environment and is passionate about building real-world ML solutions that drive  business outcomes.      Key Responsibilities : ∙Own the full ML pipeline: data ingestion, cleaning, feature engineering, model  development, deployment, and monitoring.  ∙Build and fine-tune models using Python and frameworks like Scikit-learn, XGBoost,  TensorFlow, or PyTorch.  ∙Deploy models using Databricks, MLflow, and cloud-native tools (preferably Azure).  ∙Develop robust, scalable pipelines using PySpark or native Databricks workflows.  ∙Collaborate with BI analysts and business stakeholders to translate requirements into  production-ready solutions.  ∙Maintain and improve existing models and pipelines with minimal supervision.      Required Skills : ∙3+ years of experience in applied data science or ML engineering.  ∙Strong Python programming skills, including experience with data manipulation and ML libraries.  ∙Experience with Databricks and cloud-based ML deployment (Azure preferred).  ∙Ability to work independently across the full stack of ML development and deployment.    ∙Familiarity with version control (Git), CI/CD, and MLOps best practices.  ∙Excellent communication skills and ability to work with remote teams across time zones.      Nice to Have  ∙Experience with data pipeline development using PySpark or Delta Lake.  ∙Exposure to Docker, REST APIs, or real-time inference.  ∙Prior experience working in a manufacturing or industrial analytics environment.    Interview Process:  Shortlisted candidates will be required to complete:  ∙An online technical skills assessment focused on Python and applied machine learning.  ∙An in-person practical test at our Ahmedabad Tech Center to evaluate real-world  problem-solving and deployment capabilities.  Hours: 2:30 PM – 11:30 PM IST (working from Office) Reports to: Manager, Data Analytics California, USA 

Key Responsibilities: - 1. Model Development: Design, build, and optimize supervised, unsupervised, and deep learning models for various business problems. 2. Data Exploration & Feature Engineering: Clean, transform, and analyze structured and unstructured data; identify significant features. 3. AI Integration: Develop end-to-end AI pipelines and integrate models into production systems ...

Responsibilities As a Senior ML Engineer, you will lead the design, development, and deployment of advanced computer vision systems that power AI automation across diverse operational workflows. You will take ownership of the entire solution lifecycle, from problem scoping, model development, to deployment and performance monitoring, with a team of ML engineers. Lead design and ...

    Key Responsibilities: Design, develop, and implement end-to-end computer vision models Work on use cases such as image classification, object detection, pose estimation, OCR, facial recognition, etc. Apply deep learning techniques using CNNs, GANs, and transformers for vision-based tasks Handle large-scale visual data and optimize pipelines for training, inference, and deployment Collaborate with cross-functional teams including software ...

JOB SUMMARYLooking for highly skilled and experienced Senior Data Architect. As a Senior Data Architect,you will play a critical role in designing, implementing, and managing data architecture,ensuring it supports both current needs and future aspirations in data and AI. This rolerequires a deep understanding of data architecture principles, data modelling ...

Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space 3.5 - 7 Years of relevant experience in the space Expertise in mining AI/ML opportunities from open ended business problems and drive solution design/development while closely collaborating with engineering, product ...

BASIC PURPOSE: The primary responsibilities of the AWS Machine Learning Engineer are to design, develop and deploy Machine learning models using AI/ML technologies within the AWS framework. This role will collaborate closely with the product and software development teams to operationalize these ML solutions for automating key business processes across the ...

Job Profile -  MLOps Engineer   Location -  Bangalore   Type - Permanent Full Time   Experience - 5 to 7 years   Key Skiils - Artifactory Register, Terraform, GCP, CI/CD, Containerization     Job Description   Mandatory Experience in Terraform, GCP infrastructure, CI/CD deployment, Artifactory registry and containerization   Design, build applications using containerization and orchestration with Docker and Kubernetes and cloud platforms.   Demonstrated experience with containerization, ...

Must Have Skills: ML Engineer, Snowflake & MLflowExternal Description:We are seeking an ML Engineer with strong expertise in deploying, monitoring, and managing machine learning pipelines on Snowflake. The ideal candidate will act as a bridge between the Data Engineering team and the ML team, ensuring seamless integration of ML models into ...