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AIML Engineer

Onelab Ventures
per Month
Full Time
IT - Software
4 months ago
Jobs by Experience
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1-3years

Job Location
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Monthly Salary
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Not Disclosed

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Salary Not Disclosed

Vacancy


1 Vacancy

Posted on :

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:

Overview:
We are looking for a talented and motivated AI/ML Engineer to join our team and contribute to the development and deployment of cuttingedge artificial intelligence (AI) and machine learning (ML) solutions. The ideal candidate will have a strong background in machine learning algorithms data processing techniques and cloud services. This role requires handson experience in building deploying and optimizing machine learning models and working in a collaborative crossfunctional team environment.

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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