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Machine Learning Engineer Job Description Job Summary We are seeking a skilled and motivated Machine Learning Engineer to join our growing team in Chennai. This role offers an exciting opportunity to contribute to cutting-edge projects within the IT / Technology industry. Key Responsibilities The Machine Learning Engineer will be responsible for designing, developing, and deploying machine learning models and pipelines. This includes collaborating with cross-functional teams to identify and solve complex business problems using data-driven solutions. Required Skills & Qualifications AI/ML : A strong understanding of artificial intelligence and machine learning principles, including various algorithms and techniques. Scikit-learn : Proficiency in utilizing Scikit-learn for model building, evaluation, and selection. PyTorch : Experience with PyTorch for deep learning model development and training. TensorFlow : Familiarity with TensorFlow for building and deploying large-scale machine learning models. LLM : Knowledge of Large Language Models (LLMs) and their applications. ETL : Experience with Extract, Transform, Load ( ETL ) processes for data preparation and integration. Big Query : Ability to work with Big Query for data warehousing and querying. Data Flow : Understanding of Data Flow concepts and their application in data processing. Python : Strong programming skills in Python for data analysis, machine learning, and scripting. Airflow : Experience with Airflow for orchestrating and scheduling data pipelines. PySpark : Proficiency in PySpark for distributed data processing and machine learning. SQL : Expertise in SQL for data querying and manipulation. GCS : Familiarity with Google Cloud Storage ( GCS ) for data storage and management. GitHub : Experience using GitHub for version control and collaboration. CI/CD : Knowledge of Continuous Integration and Continuous Deployment ( CI/CD ) practices. Dynatrace : Experience with Dynatrace for application performance monitoring. Analytical Skills : Exceptional analytical and problem-solving skills with the ability to interpret data and draw meaningful conclusions. Software Engineering : Solid foundation in software engineering principles and best practices. Design Practices : Understanding of software design patterns and principles. Documentation : Ability to create clear and concise technical documentation. DevOps : Familiarity with DevOps methodologies and tools. Pair Programming : Experience with Pair Programming techniques for collaborative development. TDD : Knowledge of Test-Driven Development ( TDD ) principles. Agile Ceremonies : Experience participating in Agile Ceremonies . PI Planning : Understanding of PI Planning within an Agile framework. Experience Required: 4 - 10 years of relevant experience. We are seeking a candidate with a proven track record of building and deploying machine learning solutions. This level of experience should demonstrate a strong understanding of the entire machine learning lifecycle, from data collection and preparation to model deployment and monitoring. What We Offer Salary:
Job Summary We are seeking a highly motivated and skilled Artificial Intelligence Senior Associate to join our growing team in India. This role is ideal for a candidate with a strong foundation in data science and a passion for leveraging AI/ML to solve complex business challenges within the Technology industry. Key Responsibilities The Artificial Intelligence Senior Associate will be responsible for a range of tasks related to the development, implementation, and maintenance of AI/ML solutions. This includes collaborating with cross-functional teams to identify opportunities for AI/ML applications, designing and building AI/ML models, and ensuring the scalability and reliability of these models in a production environment. The role requires a proactive approach to problem-solving and a commitment to continuous improvement. Required Skills & Qualifications AI/ML : A deep understanding of artificial intelligence and machine learning principles, including various algorithms and techniques for model building, training, and evaluation. Python : Proficiency in Python programming language for data manipulation, statistical analysis, and AI/ML model development. Google Cloud Platform (GCP) : Experience with GCP services, including Big Query , Dataproc , Data Fusion , and Cloud SQL , for data storage, processing, and analysis. Data/Analytics : Strong analytical skills with the ability to extract meaningful insights from large datasets and communicate findings effectively. Automation : Experience in automating data processing and AI/ML workflows to improve efficiency and reduce errors. Business Analysis : Ability to understand business requirements and translate them into technical specifications for AI/ML solutions. Business Transformation : A grasp of how AI/ML can be leveraged to drive business transformation and create competitive advantage. CI/CD : Familiarity with continuous integration and continuous delivery ( CI/CD ) practices for deploying and managing AI/ML models. ETL : Experience with extract, transform, load ( ETL ) processes for data integration and preparation. Jira : Proficiency in using Jira for project management and issue tracking. Data Flow : Understanding of data flow principles and techniques for designing efficient data pipelines. TERRAFORM : Experience with TERRAFORM for infrastructure as code. Tekton : Knowledge of Tekton for container-native CI/CD. AIRFLOW : Experience with AIRFLOW for orchestrating complex data workflows. Airflow PySpark : Ability to utilize Airflow with PySpark for large-scale data processing. POSTGRES : Familiarity with POSTGRES database. API : Understanding of API design and integration. GCP : Comprehensive knowledge of GCP ecosystem. Financial Reporting : Ability to apply AI/ML techniques to financial data and generate insightful reports. Leadership : Demonstrated leadership potential with the ability to guide and mentor junior team members. Strategic Communication : Excellent communication skills with the ability to present complex technical concepts to both technical and non-technical audiences. Communication Skills : Strong written and verbal communication skills. Analytical Skills : Exceptional analytical and problem-solving skills. Problem-Solving Skills : Ability to identify, analyze, and solve complex problems effectively. GitHub : Proficiency in using GitHub for version control and collaboration. Qualifications : A Bachelor's Degree and a Master's Degree are required. Experience Required : We are seeking candidates with 3-9 years of relevant experience in data science or a related field. This level of experience indicates a strong foundation in AI/ML principles and a proven ability to deliver impactful results. What We Offer Salary :
Job Summary We are seeking a skilled and motivated Machine Learning Engineering Engineer 2 to join our growing team. This role is ideal for an individual with a strong foundation in machine learning principles and a passion for building and deploying innovative solutions within the IT / Technology industry. Key Responsibilities The responsibilities of this role will encompass a range of tasks related to the development, implementation, and maintenance of machine learning models and pipelines. The candidate will collaborate with cross-functional teams to ensure the successful integration of machine learning solutions into our existing infrastructure. Required Skills & Qualifications AI/ML: Demonstrated proficiency in Artificial Intelligence and Machine Learning concepts, including model selection, training, evaluation, and deployment. Scikit-learn: Experience utilizing Scikit-learn for various machine learning tasks, including data preprocessing, model selection, and evaluation. PyTorch: Familiarity with PyTorch , a widely used deep learning framework, for building and training complex neural networks. TensorFlow: Experience with TensorFlow , another popular deep learning framework, for developing and deploying machine learning models at scale. LLM: Understanding of Large Language Models ( LLM ) and their applications. ETL: Knowledge of ETL (Extract, Transform, Load) processes for data preparation and integration. Big Query: Experience with BigQuery for querying and analyzing large datasets. Data Flow: Familiarity with Data Flow for building and managing data processing pipelines. Python: Strong programming skills in Python , a versatile language widely used in machine learning. Airflow: Experience with Airflow for orchestrating and scheduling complex data workflows. PySpark: Proficiency in PySpark for distributed data processing and machine learning. SQL: Solid understanding of SQL for data querying and manipulation. GCS: Experience with GCS (Google Cloud Storage) for storing and managing data in the cloud. GitHub: Familiarity with GitHub for version control and collaborative development. CI/CD: Understanding of CI/CD (Continuous Integration/Continuous Deployment) principles and practices. Dynatrace: Experience with Dynatrace for application performance monitoring. Analytical Skills: Strong analytical and problem-solving skills, with the ability to interpret data and draw meaningful conclusions. Software Engineering: Solid foundation in Software Engineering principles and best practices. Design Practices: Knowledge of software design patterns and principles. Documentation: Ability to create clear and concise technical documentation. DevOps: Understanding of DevOps methodologies and practices. Pair Programming: Experience with Pair Programming techniques for collaborative code development. TDD: Familiarity with TDD (Test-Driven Development) methodologies. Agile: Experience working within an Agile development environment. Education: Bachelor's Degree required. Experience: 1 - 4 years of relevant experience. This level is expected to be a mid-level contributor, capable of working independently and contributing to team goals. What We Offer Salary:
Exp: 6+ Location: Any CGI Budget : 22 LPA Kotlin Java 21 JPA in combination with Hybernate Relational databases / SQL Spring Framework 6 Open API and Open API code generation REST APIs Database migrations via Flyway GitHub Actions Azure Environment Gradle as build system JUnit 5 for unit tests Testcontainers End-2-end tests using Playwrite Soft skills High degree of independence Willingness and ability to acquire knowledge on their own Open communication with team and client
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