About the Job :

We are seeking a Senior AI Engineer to design, architect, and deploy advanced AI systems at scale, combining modern machine learning techniques with classical AI approaches such as expert systems, knowledge representation, and intelligent control to deliver real world business impact.

Key Responsibilities :

- Design and implement production grade machine learning systems from research to deployment.

- Develop expert systems and decision support frameworks using neural and symbolic AI techniques.

- Architect rule based reasoning engines integrated with knowledge graphs.

- Build intelligent control systems and adaptive automation for dynamic environments.

- Create scalable data pipelines, APIs, and model serving infrastructure.

- Optimize AI systems for accuracy, performance, efficiency, and explainability.

- Establish and maintain MLOps best practices ensuring reproducibility and reliability.

- Collaborate with product, engineering, and research teams to translate AI capabilities into business outcomes.

Skills Required :

Machine Learning Foundation :

- Strong understanding of deep learning architectures, optimization techniques, and statistical modeling.

- Hands on production experience with PyTorch or TensorFlow.

- Advanced Python programming and solid software engineering principles.

- Proven experience deploying, monitoring, and maintaining AI models at scale.

- Experience with cloud platforms such as AWS, GCP, or Azure and end to end MLOps workflows.

Classical AI Systems :

- Experience designing and implementing expert systems and inference engines.

- Strong background in decision support systems with optimization and human in the loop workflows.

- Knowledge of adaptive control systems, real time decision making, and automation.

- Experience with rule based systems, ontology design, semantic modeling, and knowledge graphs.

Technical Skills :

- Experience with transformer architectures and large language models.

- Knowledge of distributed training and inference optimization.

- Experience with vector databases, retrieval systems, RAG pipelines, RLHF, and agent frameworks.

- Familiarity with ML tooling such as Weights and Biases, Ray, Kubeflow.

- Experience with graph databases like Neo4j, Amazon Neptune, or RDFox.

- Knowledge of rule engines such as Drools, CLIPS, or Jess.

- Understanding of semantic web technologies including RDF, OWL, SHACL, SPARQL, and Cypher.

- Exposure to neuro symbolic AI architectures and explainable AI frameworks.

- Knowledge of process control systems such as PLC, SCADA, or industrial automation systems.

Qualifications :

- Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field.

- 5 to 8 plus years of hands on experience in AI and machine learning systems.

- Strong exposure to both modern machine learning and classical AI methodologies.

What Sets You Apart :

- Ability to bridge neural and symbolic AI with strong judgment and problem solving skills.

- Balance between innovation and practical system design.

- Strong coding standards with clean, maintainable, and well tested code.

- Ability to communicate complex AI concepts to both technical and non technical stakeholders.

- Open source contributions or research publications in AI related fields.

- Commitment to explainability, transparency, and responsible AI development.

What We Offer :

- Competitive compensation with potential equity.

- Opportunity to work on challenging AI problems with real world impact.

- Access to strong computing infrastructure and modern AI tooling.

- Collaborative and learning driven work culture.

- Opportunity to shape the future of hybrid and intelligent AI systems.