19 Job openings found

Develop, maintain, and optimize forecasting Machine Learning (ML) models for better accuracy. Collaborate with other data scientists and data engineers to ensure that specifications are translated into flexible, scalable, and maintainable solutions. Research and stay abreast of state-of-the-art machine learning technologies. Follow code standards and best practices. 7-8 years’ experience in ...

Role Overview As a Senior Platform Engineer – MLOps, you will play a key role in designing, building, and maintaining the infrastructure and workflows that support our machine learning systems. You’ll work closely with data scientists, ML engineers, and DevOps teams to implement scalable MLOps solutions, mentor team members, and ensure smooth deployment and ...

Key Responsibilities  Model Development & Training  ○ Design, train, and fine-tune deep learning and machine learning models (transformers, CNNs, RNNs, gradient boosting, etc.).  ○ Implement data preprocessing pipelines, feature extraction, and  augmentation techniques.  ○ Conduct hyperparameter optimization and experiment management. ● Evaluation & Optimization  ○ Run model evaluations, benchmark against baselines, and perform ablation studies.  ○ ...

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 

Hi All,   We are Hiring for AI/ML Engine AI/ML Engineer responsible for building core ML infrastructure that powers adaptive learning for 100K+ students  Develop recommendation engines, predictive analytics, computer vision, and NLP systems using Python, TensorFlow, and PyTorch.   Task:   Design and train ML models for student behavior prediction and content recommendation Build recommendation systems, personalizing study ...

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 ...

Position Overview  We are seeking a highly skilled and forward-thinking AI Engineer specialized in Large Language Models (LLMs) to design, develop, and deploy innovative AI-powered applications and intelligent agents. The ideal candidate will possess deep expertise in LLM engineering, including advanced prompt engineering strategies, fine-tuning, evaluation methodologies, and the development of ...

Role Overview:We are seeking a passionate and hands-on Gen AI Lead who is deeply experienced in the latestdevelopments in Generative AI (including LLMs, RAG, LoRA, QLoRA, etc.), with a strong foundationin Computer Vision, Image Processing, and Video Analytics. This individual will play a pivotal role indesigning, architecting, and deploying full-stack ...

  Experience Range: 5 to 12 yrs (min 4 years relevant) Responsibilities: Enable Model tracking, model experimentation, Model automation Develop ML pipelines to support  Develop MLOps components in Machine learning development life cycle using Model Repository (either of): MLFlow, Kubeflow Model Registry Machine Learning Services (either of): Kubeflow, DataRobot, HopsWorks, Dataiku or any relevant ML E2E PaaS/SaaS. Work ...

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, ...