Senior AI Engineer

Role Overview :

We are seeking a highly skilled Senior AI Engineer to design, develop, and deploy advanced AI / ML solutions that solve complex business challenges and power next-generation products. The ideal candidate has strong expertise in machine learning, deep learning, and generative AI, with proven experience building scalable systems in production environments.

As a senior member of the team, you will play a hands-on technical role while also mentoring junior engineers, contributing to architectural decisions, and collaborating with cross-functional teams to integrate AI into real-world applications.

Key Responsibilities :

AI / ML Solution Development

Design, build, and optimize machine learning and deep learning models (supervised, unsupervised, reinforcement learning, generative AI).

Implement end-to-end pipelines, including data ingestion, preprocessing, model training, evaluation, and deployment .

Work with large datasets, structured and unstructured, applying feature engineering and advanced ML techniques.

Research and prototype cutting-edge AI methods (LLMs, RAG, multimodal AI, computer vision, NLP).

Systems Engineering & Deployment

Develop scalable, production-grade AI services and APIs.

Apply MLOps best practices : model versioning, CI / CD pipelines, monitoring, and retraining workflows.

Optimize models for latency, scalability, and cost efficiency in cloud (AWS, Azure, GCP) or hybrid environments.

Ensure solutions are secure, resilient, and compliant with data governance standards.

Collaboration & Leadership

Partner with data scientists, product managers, and software engineers to translate business needs into AI solutions.

Mentor junior engineers and contribute to building a high-performance AI engineering culture .

Influence architectural decisions on AI / ML platforms, frameworks, and tools.

Contribute to technical documentation, design reviews, and coding best practices.

Innovation & Continuous Learning

Stay current with AI research, frameworks, and tools, and assess their potential adoption.

Experiment with generative AI and emerging technologies to enhance organizational capabilities.

Advocate for responsible and ethical AI practices.

Qualifications & Experience :

Bachelor’s or Master’s in Computer Science, AI / ML, Data Science, or related field (PhD preferred).

5–8 years of experience in AI / ML engineering with a proven track record of delivering production systems.

Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, JAX).

Proficiency in Python (and optionally C++ / Java for performance-critical components).

Strong background in data engineering (SQL / NoSQL, Spark, Kafka, or similar).

Experience with cloud ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI).

Strong knowledge of MLOps tools (Kubeflow, MLflow, Airflow, Docker, Kubernetes).

Expertise in NLP, computer vision, or generative AI is highly desirable.

Familiarity with vector databases (Pinecone, Weaviate, FAISS) and RAG architectures.