Machine Learning Specialist

5 years

0 Lacs

Posted:13 hours ago| Platform: Linkedin logo

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On-site

Job Type

Contractual

Job Description

About Client :

Our client is one of the world's fastest-growing AI companies, accelerating the advancement and deployment of powerful AI systems. They helps customers in two ways: Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies. Powering this growth is our clients talent cloud—an AI-vetted pool of 4M+ software engineers, data scientists, and STEM experts who can train models and build AI applications. All of this is orchestrated by ALAN—our AI-powered platform for matching and managing talent, and generating high-quality human and synthetic data to improve model performance. ALAN also accelerates workflows for model and agent evals, supervised fine-tuning, reinforcement learning, reinforcement learning with human feedback, preference-pair generation, benchmarking, data capture for pre-training, post-training, and building AI applications.


Job Title: Python Service Implementation

Location: Hyderabad

Experience: 5+ years

Employment Type: Contract to hire

Notice Period: Immediate joiners



Requriment:

  • Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related quantitative field.
  • 3+ years of hands-on ML development experience
  • Proficiency in at least some of the ML areas and frameworks, including:
  • Supervised learning (classification, regression, …)
  • Unsupervised learning (clustering, anomaly detection, …)
  • Time-series analysis
  • Natural Language Processing (NLP)
  • Computer Vision (CV)
  • Statistical modeling
  • Ability to understand and apply different models to real-world use cases
  • Hands-on experience with DS and ML solutions in production environments
  • Strong understanding of data cleaning and wrangling, feature engineering, model optimization, and evaluation metrics
  • Proficiency in Python and its common data science libraries (e.g., Pandas, NumPy, Scikit-learn)

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