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AIML Engineer
1-3years
–
Not Disclosed
Salary Not Disclosed
1 Vacancy
15-10-2024
Job Description
Company Description
Onelab Ventures is a software development company that partners with startups and enterprises to create successful scalable products. With over 100 products built we have a strong track record of delivering innovative solutions in AI LLM (Large Language Models) SaaS Fin tech and Healthcare . Our agile collaborative approach ensures that client visions are transformed into reliable userfriendly products using the latest technologies and methodologies.
Job Description:
Key Responsibilities:
- Machine Learning Model Development:Design develop and implement machine learning models and algorithms to solve realworld problems and improve business processes.
- Data Preprocessing:Work with large complex datasets by cleaning organizing and preparing the data for training and validation of machine learning models.
- Model Training and Tuning:Train machine learning models using frameworks like TensorFlow PyTorch or Scikitlearn and finetune models to improve accuracy and performance.
- Deployment and Maintenance:Deploy models into production environments using platforms such as AWS SageMaker Azure ML or Google AI and monitor their performance in realtime applications.
- AI Research:Stay updated on the latest research in machine learning and AI and apply relevant findings to improve model accuracy efficiency and scalability.
- Collaboration:Work closely with data scientists data engineers and software developers to integrate AI models into existing systems and workflows.
- Model Evaluation and Optimization:Use evaluation metrics such as accuracy precision recall F1score and ROCAUC to assess model performance and identify opportunities for improvement.
- Automation:Automate data workflows and model training pipelines using cloud services like AWS Azure or GCP and tools such as Docker and Kubernetes.
- Documentation:Maintain clear and concise documentation of the models pipelines and processes developed ensuring they can be understood and maintained by the team.
Requirements
Key Skills and Qualifications:
- Experience:25 years of experience in AI/ML development with a focus on building training and deploying machine learning models in a production environment.
- Programming Skills:Proficiency in programming languages such as Python R or Java. Experience with machine learning libraries like TensorFlow PyTorch or Scikitlearn.
- Data Management:Strong understanding of databases data structures and ETL processes. Experience working with SQL NoSQL or other databases.
- Cloud Experience:Handson experience with cloud platforms like AWS Azure or Google Cloud particularly in deploying machine learning models and managing infrastructure.
- Containerization:Knowledge of Docker and Kubernetes for containerizing machine learning applications and managing largescale deployments.
- Modeling:Solid understanding of supervised and unsupervised learning techniques deep learning natural language processing (NLP) and reinforcement learning.
- ProblemSolving:Strong analytical skills and the ability to think critically about how to solve complex problems with machine learning solutions.
- Communication:Excellent communication and collaboration skills to work with crossfunctional teams and convey technical information to nontechnical stakeholders.
Preferred Qualifications:
- Education:Bachelor s or Master s degree in Computer Science Data Science Engineering or a related field. A Ph.D. in a relevant area is a plus.
- Certifications:Certifications in AI/ML such as AWS Certified Machine Learning Specialty Microsoft Certified Azure AI Engineer or Google Professional ML Engineer are highly desirable.
- Tools and Frameworks:Experience with tools like Jupyter Git and MLflow for model versioning and experimentation tracking.
Key Skills and Qualifications: Experience: 2-5 years of experience in AI/ML development, with a focus on building, training, and deploying machine learning models in a production environment. Programming Skills: Proficiency in programming languages such as Python, R, or Java. Experience with machine learning libraries like TensorFlow, PyTorch, or Scikit-learn. Data Management: Strong understanding of databases, data structures, and ETL processes. Experience working with SQL, NoSQL, or other databases. Cloud Experience: Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud, particularly in deploying machine learning models and managing infrastructure. Containerization: Knowledge of Docker and Kubernetes for containerizing machine learning applications and managing large-scale deployments. Modeling: Solid understanding of supervised and unsupervised learning techniques, deep learning, natural language processing (NLP), and reinforcement learning. Problem-Solving: Strong analytical skills and the ability to think critically about how to solve complex problems with machine learning solutions. Communication: Excellent communication and collaboration skills to work with cross-functional teams and convey technical information to non-technical stakeholders. Preferred Qualifications: Education: Bachelor s or Master s degree in Computer Science, Data Science, Engineering, or a related field. A Ph.D. in a relevant area is a plus. Certifications: Certifications in AI/ML, such as AWS Certified Machine Learning Specialty, Microsoft Certified Azure AI Engineer, or Google Professional ML Engineer, are highly desirable. Tools and Frameworks: Experience with tools like Jupyter, Git, and MLflow for model versioning and experimentation tracking.
Employment Type
Full Time
Company Industry
Key Skills
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