Drive innovation in AI/ML systems with cutting-edge technologies and frameworks. Collaborate remotely with dynamic teams to deliver impactful solutions. Advance your career in a challenging and rewarding environment.
Ai/Ml Engineer
in Information Technology PermanentJob Detail
Job Description
Overview
- Develop and deploy cutting-edge machine learning and Generative AI systems for impactful business solutions.
- Collaborate with cross-functional teams to translate business requirements into scalable AI/ML solutions.
- Focus on building advanced applications leveraging structured and unstructured data for optimized decision-making.
- Maintain and monitor machine learning models and pipelines ensuring reliability and performance.
- Contribute to the development of AI engineering standards and best practices across the organization.
- Work in a fully remote environment with opportunities for professional growth and collaboration.
Key Responsibilities & Duties
- Design and develop machine learning and LLM-powered systems using modern architectures and frameworks.
- Optimize data pipelines for feeding traditional ML models and LLM-based systems.
- Implement and monitor model and data quality checks ensuring system accuracy and consistency.
- Conduct machine learning tests and experiments, documenting findings and results.
- Collaborate with stakeholders to align AI/ML solutions with business objectives.
- Provide technical guidance and support for AI/ML initiatives across the organization.
- Create and maintain documentation for ML and GenAI systems, including evaluation frameworks and architectural decisions.
Job Requirements
- Bachelor’s degree in Computer Science, Mathematics, or related field; Master’s degree preferred.
- Minimum 3 years of experience in machine learning engineering; 5 years preferred.
- Proficiency in SQL, Databricks, AWS services, Python, and Spark.
- Experience with ML frameworks such as XGBoost, Scikit-learn, TensorFlow, Keras, or PyTorch.
- Hands-on experience deploying LLM-powered applications and utilizing MLOps/LLMOps tooling.
- Strong analytical and problem-solving skills with the ability to derive insights from complex data sets.
- Effective communication skills for conveying technical information to non-technical stakeholders.
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