Amantya Technolgies - Artificial Intelligence/Machine Learning Engineer

2-5 Years

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Early Applicant

Job Description

Description

Key Qualifications :

Technical Skills

Strong Work Experience of 2-5 years in AI domain
Strong programming skills in Python (preferred), with proficiency in libraries like TensorFlow, PyTorch, or Scikit-learn.
Knowledge of ML operations (MLOps) and experience in deploying models in production environments.
Solid understanding of traditional ML models (e.g., regression, SVM, decision trees, random forests).
Exposure to large language models (e.g., OpenAI GPT, Llama, BERT) and fine-tuning techniques.
Familiarity with NLP techniques, transformers, and generative AI models.

Data Expertise

Architecture And Systems

Understanding of software architecture and experience contributing to system design.
Knowledge of CI/CD pipelines for AI/ML projects.
Familiarity with cloud platforms (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes) would be a big plus .

Soft Skills

Education

Key Responsibilities

AI/ML Development :

Design, implement, and optimize AI pipelines, including data ingestion, preprocessing, model training, and deployment.
Develop and fine-tune traditional machine learning models and integrate them into production systems.
Work on cutting-edge projects involving LLMs, including prompt engineering, fine-tuning, and inference optimization.

Data Engineering

Perform data cleanup and preprocessing, ensuring data quality and consistency.
Develop and implement feature engineering pipelines to enhance model performance.
Collaborate with data engineers to manage large-scale datasets efficiently.

Software Development

Write clean, maintainable, and efficient code in programming languages such as Python, or Go.
Build scalable, robust, and maintainable solutions for AI/ML models and their deployment.
Contribute to architecture design and participate in code reviews to ensure best practices.

Collaboration And Communication

Clearly communicate technical concepts and progress to both technical and non-technical stakeholders.
Act as a team player, contributing to a collaborative and innovative work environment.

Continuous Learning

Stay updated on the latest developments in AI/ML, including advancements in LLMs and model optimization techniques.
Explore and evaluate emerging AI tools and technologies for potential integration into workflows.

(ref:hirist.tech)