Ai/ML Engineer

Job Overview

Datum Labs is seeking a passionate and results-driven AI/ML Engineer to develop, deploy, and optimize cutting-edge AI models. In this role, you will work on deep learning, generative AI, and neural representation learning, contributing to real-world applications in AI-driven data intelligence. You will collaborate with cross-functional teams, participate in customer-facing discussions, and ensure our models deliver actionable insights that drive business value.

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Key Responsibilities

• Design, train, and fine-tune AI models, including LLMs, diffusion models, and neural networks.

• Build and enhance data pipelines & ETL workflows in collaboration with data engineers.

• Optimize deep learning models for scalability, efficiency, and performance.

• Implement and manage vector databases (Weaviate, Pinecone) for AI applications.

• Collaborate with cross-functional teams to align AI initiatives with business objectives.

• Ensure model explainability, fairness, and bias mitigation for responsible AI practices.

• Lead customer discussions, providing insights and actionable recommendations.

• Deploy models in production with intuitive, user-friendly interfaces.

• Implement MLOps practices for model monitoring, retraining, and lifecycle management.

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Requirements

• Strong proficiency in Python and relevant libraries (PyTorch, TensorFlow, Pandas, NumPy).

• Hands-on experience with LLMs, Generative AI, Hugging Face Transformers, Diffusers.

• Knowledge of prompt engineering, model optimization, and fine-tuning techniques.

• Experience with data analysis, unstructured datasets, and model visualization tools.

• Familiarity with APIs for model integration (e.g., FastAPI, Flask).

• Solid grasp of SQL for structured data analysis.

• Understanding of cloud-based ML tools (e.g., AWS SageMaker, Azure ML, GCP Vertex AI).

• Proficiency in version control systems like Git.

• Strong problem-solving skills with a keen eye for detail.

• Excellent communication and presentation skills for technical and non-technical stakeholders.

• Bachelor’s/Master’s in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

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Nice-to-Have

• Experience with distributed computing, GPU acceleration, and parallel processing.

• Knowledge of statistical modeling, Bayesian inference, and neural network architectures.

• Familiarity with CI/CD pipelines for ML model deployment.

• Exposure to MLOps tools like MLflow or Kubeflow.‍

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Perks & Benefits

• Competitive Salary: Market-competitive compensation based on experience.

• Performance-Based Bonuses: Incentives tied to performance and contribution.

• Career Growth: Opportunities for continuous learning and professional development.

• Flexible Learning Support: Access to certifications, conferences, and learning platforms.

• Collaborative Culture: Be part of a dynamic, innovation-driven team.

• Team Building Activities: Regular team retreats, workshops, and learning sessions.

Join us at Datum Labs and contribute to building state-of-the-art AI models that help companies make data-driven decisions with confidence.

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How to Apply:

Submit your resume and a brief cover letter highlighting your experience and projects to careers@datumlabs.ai.