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Machine Learning Engineer Graduate Jobs in Pune

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Urgent Requirement For Senior ML Engineer

Impact HR & KM Solutions

  • 4 - 6 yrs
  • 6.5 Lac/Yr
  • Pune
ML Engineer ML
Key ResponsibilitiesDesign, develop, and deploy scalable machine learning models and algorithmsWork with large datasets to build data pipelines and preprocessing systemsDevelop and optimize predictive models and recommendation systemsDeploy ML models into production and monitor performanceWork on model training, testing, evaluation, and tuningCollaborate with data scientists, developers, and business teamsImplement MLOps practices for model lifecycle managementEnsure model accuracy, scalability, and efficiencyStay updated with latest ML technologies and frameworks
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AI/ML Engineer

Kasa Talent Pvt Ltd

  • Fresher
  • 4.0 Lac/Yr
  • Pune
Data Analysis C++ Python LLM AWS Google Cloud Azure AI SQL Data Cleaning
We are seeking a talented AI/ML Engineer to design, develop, and deploy machine learning models that solve real-world business problems.Key ResponsibilitiesDevelop, train, and optimize machine learning and deep learning models.Design and implement AI solutions for automation, prediction, and data analysis.Work with large datasets to clean, preprocess, and engineer features.Deploy models into production environments and monitor performance.Build scalable ML pipelines and integrate models with applications.Conduct experiments, model evaluations, and performance tuning.Collaborate with cross-functional teams including data engineers and product managers.Stay updated with the latest research and advancements in AI/ML.Note: Only Pune-based candidates can eligible to apply.
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Looking For ML Engineer

The Supreme Consultancy

Machine Learning Data Analysis Python ML Engineer Data Science Data Analyst Problem Sloving Deep Learning Deep Learning Engineer
Mandatory Criteria (Can't be neglected during screening) : Looking for Only BTech and BE candidates. Candidate should have Hands-on development experience as Data Analyst and/or ML Engineer. Candidate must have Coding experience in Python. Need candidates with atleast 1-2years of ML experience. Candidate should have Good Experience with ML models and ML algorithms. Need Experience with statistical modelling of large data sets. Looking for Immediate joiners or max. 30 days of Notice Period candidates. The candidates based out of these locations - Bangalore, Pune, Hyderabad, Mumbai, will be preffered. Kindly note Salary bracket will vary according to the exp. of the candidate - - Experience from 4 yrs to 5 yrs - Salary range - 15 LPA - 21 LPA max.- Experience from 6 yrs to 7 yrs - Salary range - 21 LPA - 25 LPA- Experience of 8 yrs to 9 yrs - Salary range - 30 LPA - 32 LPA- Experience 10 yrs to 12 yrs - Salary upto 40 LPA max.What You will do: Play the role of Data Analyst / ML Engineer Collection, cleanup, exploration and visualization of data Perform statistical analysis on data and build ML models Implement ML models using some of the popular ML algorithms Use Excel to perform analytics on large amounts of data Understand, model and build to bring actionable business intelligence out of data that is available in different formats Work with data engineers to design, build, test and monitor data pipelines for ongoing business operationsBasic Qualifications: Only BTech and BE candidates. Experience: 4+ years. Hands-on development experience playing the role of Data Analyst and/or ML Engineer. Experience in working with excel for data analytics Experience with statistical modelling of large data sets Experience with ML models and ML algorithms Coding experience in PythonNice to have Qualifications: Experience with wide variety of tools used in ML Experience with Deep learningBenefits: Competitive salary. Hybrid work model. Learning and gaining experience rapidly. Reimbursement for basic working set up at home. Insurance (including a top up insurance for COVID).
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Data/ML Platform Engineer

Onactive

Python SQL ML Docker AWS Cloud Engineer
Level of skills and experience:5 years of hands-on experience in using Python, Spark,Sql.Experienced in AWS Cloud usage and management.Experience with Databricks (Lakehouse, ML, Unity Catalog, MLflow).Experience using various ML models and frameworks such as XGBoost, Lightgbm, Torch.Experience with orchestrators such as Airflow and Kubeflow.Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes).Fundamental understanding of Parquet, Delta Lake and other data file formats.Proficiency on an IaC tool such as Terraform, CDK or Cloud Formation.Strong written and verbal English communication skill and proficient in communication with non-technical stakeholderst
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ML Engineer

Rivendell Technologies Inc

Machine Learning ML Engineer
***Responsibilities:***1. Contribute to the development of software and solutions, emphasizing ML/NLP as a key component, to productize research goals and deployable services.2. Collaborate closely with the frontend team and research team to integrate machine learning models into deployable services.3. Utilize and develop state-of-the-art algorithms and models for NLP/ML, ensuring they align with the product and research objectives.4. Perform thorough analysis to improve existing models, ensuring their efficiency and effectiveness in real-world applications.5. Engage in data engineering tasks to clean, validate, and preprocess data for uniformity and accuracy, supporting the development of robust ML models.6. Stay abreast of new developments in research and engineering in NLP and related fields, incorporating relevant advancements into the product development process.7. Actively participate in agile development methodologies within dynamic research and engineering teams, adapting to evolving project requirements.8. Collaborate effectively within cross-functional teams, fostering open communication and cooperation between research, development, and frontend teams.9. Actively contribute to building an open, transparent, and collaborative engineering culture within the organization.10. Demonstrate strong software engineering skills to ensure the reliability, scalability, and maintainability of deployable ML services.11. Take ownership of the end-to-end deployment process, including the deployment of ML models to production environments.12. Work on continuous improvement of deployment processes and contribute to building a seamless pipeline for deploying and monitoring ML models in real-world applications.
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ML Engineer

Rivendell Technologies Inc

Machine Learning ML Engineer
***Responsibilities:***1. Contribute to the development of software and solutions, emphasizing ML/NLP as a key component, to productize research goals and deployable services.2. Collaborate closely with the frontend team and research team to integrate machine learning models into deployable services.3. Utilize and develop state-of-the-art algorithms and models for NLP/ML, ensuring they align with the product and research objectives.4. Perform thorough analysis to improve existing models, ensuring their efficiency and effectiveness in real-world applications.5. Engage in data engineering tasks to clean, validate, and preprocess data for uniformity and accuracy, supporting the development of robust ML models.6. Stay abreast of new developments in research and engineering in NLP and related fields, incorporating relevant advancements into the product development process.7. Actively participate in agile development methodologies within dynamic research and engineering teams, adapting to evolving project requirements.8. Collaborate effectively within cross-functional teams, fostering open communication and cooperation between research, development, and frontend teams.9. Actively contribute to building an open, transparent, and collaborative engineering culture within the organization.10. Demonstrate strong software engineering skills to ensure the reliability, scalability, and maintainability of deployable ML services.11. Take ownership of the end-to-end deployment process, including the deployment of ML models to production environments.12. Work on continuous improvement of deployment processes and contribute to building a seamless pipeline for deploying and monitoring ML models in real-world applications.
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