
AI/ML Engineer
2 weeks ago
Working Days: From Monday to Friday Key Responsibilities:
- Lead Model Development & Deployment: Design, train, and deploy advanced machine learning models for tasks such as prediction, NLP, and deep learning, setting best practices for modeling.
- Data Architecture & Integration: Architect and optimize data storage, retrieval, and transformation workflows using PostgreSQL and other data solutions, ensuring efficient integration with ML models.
- OpenAI & NLP Innovation: Leverage OpenAI tools to develop and deploy NLP applications for text processing, summarization, sentiment analysis, and custom language models.
- Scalable ML Pipelines: Build robust, scalable data and ML pipelines, implementing MLOps practices, CI/CD, and automation for model training and deployment.
- Mentorship & Collaboration: Mentor junior team members, providing technical guidance and fostering a collaborative environment. Work closely with cross-functional teams, including data scientists, product managers, and stakeholders.
- Technical Leadership & Strategy: Contribute to the strategic direction of AI/ML initiatives, providing technical leadership on best practices, architecture, and innovation.
Requirements:
- Technical Expertise:
- Advanced proficiency in Python for machine learning, with experience in libraries like NumPy, Pandas, scikit-learn, and familiarity with TensorFlow or PyTorch.
- Deep experience with PostgreSQL for data extraction, transformation, optimization, and integration with Python.
- Proven track record of using OpenAI API and other NLP tools; expertise in prompt engineering, fine-tuning language models, and creating NLP-based solutions.
- Experience with data engineering and architecture, designing and optimizing data pipelines and workflows.
- Bachelors or Masters degree in Computer Science, Data Science, or a related field. Advanced degrees preferred.
- 5+ years of experience in machine learning engineering or data engineering roles, with a focus on building and deploying models.
- Strong analytical, problem-solving, and communication skills, with a proven ability to translate business problems into ML solutions.
- Experience with data warehousing, ETL tools, and managing data at scale.
- Proficiency in designing and implementing CI/CD pipelines.
- Knowledge of data privacy, compliance, and security best practices.
Interested candidates can apply by sharing their updated CV at- or
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