Principal AI Researcher

[Please refrain from applying if you have over 10 years of experience. This is a hands-on role that requires building from the ground up.]

Location: Bengaluru (In-Office)

Employment Type: Full-Time

About Logikality

Logikality is building an AI-native mortgage intelligence platform for the U.S. mortgage industry. We are reimagining how mortgage operations are executed by combining AI, workflow automation, and domain expertise to solve one of the most document-intensive and decision-heavy industries in the world.

Our platform goes beyond document extraction. We are building AI systems that understand mortgage files, reason across multiple sources of information, identify risks and exceptions, support underwriting and quality control decisions, and continuously improve through expert feedback and rigorous evaluation.

As we expand our AI capabilities, we are looking for a Director, AI Engineering to define and drive the research direction behind our next generation of intelligent systems.

About the Role

This is a hands-on technical leadership role for someone who enjoys solving difficult AI problems and turning research into production impact.

You will lead the research agenda across large language models, reasoning systems, agentic AI, multimodal learning, and intelligent decision support while working closely with engineering, product, and mortgage domain experts. You will prototype new ideas, validate them through rigorous experimentation, and help productionize solutions that directly improve customer outcomes.

This role is ideal for someone with deep research expertise who enjoys building real-world AI systems rather than research for its own sake.

What You'll Do

• Define and execute the Applied AI research roadmap aligned with company and product goals.
• Design novel approaches for document understanding, reasoning, planning, retrieval, and decision support.
• Build agentic AI systems capable of orchestrating tools, workflows, and domain knowledge to solve complex mortgage use cases.
• Develop multimodal AI models that combine documents, structured data, images, and operational context.
• Lead research on long-context reasoning, knowledge integration, memory, retrieval-augmented generation (RAG), and workflow automation.
• Design robust evaluation frameworks, benchmarks, and automated testing pipelines to measure model quality, reliability, explainability, and business impact.
• Rapidly prototype, experiment, and iterate on new AI techniques, evaluating state-of-the-art research for production adoption.
• Work closely with software engineers to translate research prototypes into scalable, production-ready systems.
• Mentor AI engineers and contribute to building a strong research culture within the organisation.
• Collaborate with mortgage domain experts to deeply understand operational workflows, compliance requirements, and decision-making processes.
• Stay current with advances in AI research and identify opportunities to leverage emerging techniques within our platform.
• Represent Logikality in customer interactions, strategic discussions, industry conferences, and business forums, communicating our AI vision, gathering market insights, and helping shape research priorities through direct engagement with customers and ecosystem partners.

What We're Looking For

• PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related discipline; or an engineering degree in Computer Science or related disciplines from a premier engineering institution (e.g., IITs, IISc, NITs, BITS Pilani, or top-tier global universities).
• 3–8 years of professional experience in Applied AI, Machine Learning, or AI Research, with experience building production-grade AI systems
• Strong expertise in modern AI, including Large Language Models, transformers, agentic AI, reasoning systems, retrieval, multimodal learning, or adjacent areas.
• Strong software engineering skills with Python and modern machine learning frameworks.
• Experience designing and implementing production-grade AI systems that solve complex real-world problems.
• Strong understanding of model evaluation, benchmarking, experimentation, and AI system reliability.
• Experience balancing research innovation with engineering pragmatism and product delivery.
• Excellent problem-solving and communication skills with the ability to collaborate across engineering, product, and business teams.

Why Join Logikality?

At Logikality, you'll work on problems that require genuine reasoning, not just text generation. You'll help build AI systems that understand complex documents, synthesise information across workflows, explain decisions, identify exceptions, and improve through continuous learning and expert feedback.

This is an opportunity to work at the intersection of cutting-edge AI research and real-world impact, where your ideas won't remain as papers or prototypes; they'll power intelligent systems used every day by mortgage professionals. We are looking for someone who can connect AI, platform engineering, product thinking and customer outcomes.

For the right person, this could develop into a CTO and co-founder track over the next 6–9 months, based on contribution, technical leadership and mutual fit.

Interested candidates are requested to apply via the Google Form given: https://forms.gle/jFqKzfLhNCcCFU5t9

This will be a full-time in-office role based in Bangalore. Immediate joiners are preferred.

About Naicos

Naicos, a fast-paced startup, builds AI-native products for algorithmic commerce: the future of how e-commerce runs. Our first products are already live with paying customers, and we are shipping new ones continuously.

Your Role

You will drive the research behind our imaging products, finding approaches to hard, unsolved problems in product and apparel imagery that work at production scale. You will run the experiments, prove what is viable, and hand a working approach to the engineering team.

Who We Are Looking For

•     Total experience: 3 years or more, with a strong research orientation

•     Deep learning frameworks in Python: PyTorch or TensorFlow

•     Image processing in Python: OpenCV, Pillow, scikit-image

•     Working knowledge of diffusion and other image generation models

We are looking for a strong research or research-student profile: someone who investigates, experiments and proves an approach, working closely with the AI Architect. Someone who is driven to build solutions, not just desk research.

AI Skills and Experience

•     Computer vision: classical CV alongside deep learning.

•     Segmentation, image-to-image translation, geometry and lighting; 

•     Generative imaging: diffusion models, conditioning and control, fine-tuning and LoRA,

•     Reads academic papers, judges what is reproducible, and turns one into a working prototype in days

Good to have

•     3D and rendering; published research or open-source contributions; model optimisation for inference cost

Research and innovative problem solving

•     Comfortable where there is no known answer, and defines the approach yourself

•     Solves problems inventively rather than reaching for the biggest model; many results come from classical image processing, fitment and geometric transformation

Other Relevant Skills and Experience

•     Designs experiments: baselines, measurable success criteria, honest reporting of negative results

•     Explains findings to a non-research audience and guides engineers to production

•     Git and reproducible experiment tracking (Weights & Biases, MLflow or similar)

Educational Qualification

•     BE / B.Tech / ME / M.Tech in Computer Science

•     BE / B.Tech / ME / M.Tech in any discipline with proven Computer Vision coursework or work

•     MSc / MS in Computer Science, Maths, Statistics or Computer Vision

•     PhD in Computer Vision or Machine Learning: an advantage, not a requirement

•     Reputed Tier 1 university preferred

About the Job :

We are looking for a passionate and driven AI Intern to join our dynamic team. As an intern, you will have the opportunity to work on real-world projects, develop AI models, and collaborate with experienced professionals in the field. This internship is designed to provide hands-on experience in AI and machine learning, offering you the chance to contribute to impactful projects while enhancing your skills.

Job Description:

We are seeking a talented Artificial Intelligence Specialist to join our dynamic team. As an AI Specialist, you will be responsible for developing, implementing, and optimizing AI models and algorithms. You will collaborate closely with cross-functional teams to integrate AI capabilities into our products and services. The ideal candidate should have a strong background in machine learning, deep learning, and natural language processing, with a passion for applying AI to real-world problems.

Responsibilities:

• Design, develop, and deploy AI models and algorithms.
• Conduct data analysis and pre-processing to prepare data for modeling.
• Implement and optimize machine learning algorithms.
• Collaborate with software engineers to integrate AI models into production systems.
• Evaluate and improve the performance of existing AI models.
• Stay updated with the latest advancements in AI research and apply them to enhance our products.
• Provide technical guidance and mentorship to junior team members.

Requirements:

• Any Graduate / Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field; Master's degree preferred.
• Proven experience in developing and implementing machine learning models and algorithms.
• Strong programming skills in languages such as Python, R, or Java.

Benefits :

• Internship Certificate
• Letter of Recommendation
• Performance-Based Stipend
• Part-time work from home (2-3 hours per day)
• 5 days a week, fully flexible shift

AuxoAI is hiring a Senior Applied AI Engineer to design and deploy production-grade computer vision systems that operate reliably in real-world environments.

This role focuses on building end-to-end visual intelligence systems, combining deep learning, classical computer vision techniques, and multimodal models. It is not limited to model training and requires strong ownership of system design, deployment, and real-world performance.

You will work on systems that perform perception, understanding, and reasoning over visual data, and integrate these capabilities into larger AI platforms and agent-based workflows.

You will also work on problems where existing approaches may not be sufficient, and will be expected to combine deep learning, geometric methods, and multimodal reasoning to build robust, production-grade systems.

Location – Mumbai / Bangalore / Hyderabad / Gurgaon (Hybrid – 3 days per week in office)

Responsibilities:

• Design and deploy computer vision systems for tasks such as:
• Object detection, segmentation, and tracking
• Scene understanding and structured perception
• Video understanding and temporal reasoning
• Build and optimize models using architectures such as:
• CNNs (ResNet, EfficientNet)
• Vision Transformers (ViT, Swin, DeiT)
• Detection/segmentation models (YOLO, DETR, Mask R-CNN)
• Develop multimodal systems combining vision and language:
• CLIP-style models
• Vision-language models (VLMs)
• Visual grounding and captioning systems
• Implement algorithms for:
• Multi-object tracking (SORT, DeepSORT, ByteTrack)
• Feature matching and representation learning
• Temporal modeling (RNNs, Transformers for video)
• Apply geometric and classical computer vision methods where relevant:
• Camera calibration
• Epipolar geometry
• Pose estimation
• 3D reconstruction or depth estimation
• Optimize systems for:
• Low-latency, real-time inference
• Throughput and scalability
• Edge and distributed deployment
• Design and build data pipelines for:
• Annotation workflows
• Dataset curation
• Synthetic data generation
• Integrate vision systems into:
• Multimodal AI pipelines
• Agent-based systems
• Decision-making workflows

Requirements:

• 5+ years of experience building computer vision systems in production environments
• Strong experience with deep learning frameworks (PyTorch / TensorFlow)
• Hands-on experience with:
• Detection, segmentation, or tracking systems
• Model training, fine-tuning, and evaluation
• Strong understanding of:
• Representation learning
• Loss functions (contrastive loss, focal loss, etc.)
• Evaluation metrics (mAP, IoU, precision/recall)
• Experience building and deploying end-to-end vision systems, not just training models

Candidates whose primary experience is limited to academic projects or model experimentation without real-world deployment may not be a fit for this role.

Nice to Have:

• Experience with multimodal systems (vision + language)
• Familiarity with models such as:
• CLIP, BLIP, Flamingo, or similar
• Experience with 3D vision:
• NeRFs
• SLAM
• Point clouds
• Experience with video understanding:
• Action recognition
• Event detection
• Experience building data engines:
• Active learning
• Hard negative mining
• Experience working with large-scale datasets and distributed training pipelines

Job Description:

We are seeking a versatile and highly skilled Lead AI/ML Engineer with deep expertise in Generative AI (GenAI) and Large Language Models (LLMs). This role requires a leader who can take full ownership of the

AI lifecycle—from initial architectural design to final production execution. You will lead the development of scalable AI-powered applications, demonstrating exceptional execution skills and the ability to deliver high-performance results under pressure in demanding production environments.

Machine Learning & LLM Capability:

 End-to-End ML Engineering: Build and manage comprehensive ML pipelines, including data ingestion, preprocessing, training, and evaluation using frameworks like PyTorch, TensorFlow, and Scikit-learn.  Advanced LLM Systems: Design and implement sophisticated LLM-based applications such as autonomous agents, chatbots, and complex automation tools.

 Generative AI Specialization: Architect and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases like FAISS, Pinecone, or Weaviate.

 Model Optimization: Fine-tune open-source and proprietary models (e.g., LLaMA, GPT) using advanced techniques like LoRA, QLoRA, or instruction tuning.

 Agentic Frameworks: Develop complex agentic workflows utilizing frameworks such as LangChain or LlamaIndex.

 Prompt Engineering: Implement expert-level prompt engineering, tool/function calling, and structured output generation.

 Project Ownership & Execution

 Full Lifecycle Ownership: Take complete accountability for the full ML and GenAI lifecycle, spanning data processing, model development, monitoring, and optimization.

 Architectural Leadership: Drive strategic architectural decisions for AI platforms, ensuring they are modular, scalable, and maintainable.

 Execution Excellence: Write clean, high-performance Python code following strict OOP principles and manage CI/CD pipelines for seamless project execution.

 Leadership & Mentoring: Act as a key technical leader, managing stakeholders and mentoring team members to ensure all project milestones are met with quality.

 System Integrity: Manage model and prompt versioning, experiment tracking, and comprehensive documentation for all pipelines and workflows.

 Performance Under Pressure

 Production Reliability: Ensure all AI systems maintain extreme scalability and performance under heavy production workloads, including both batch and real-time processing.

 High-Pressure Optimization: Rapidly optimize inference latency and system costs for ML and LLM systems to meet urgent business and technical requirements.

 Proactive Problem Solving: Apply strong analytical thinking to address complex challenges such as system drift, hallucinations, and latency in fast-paced environments.

 Robust Guardrails: Implement and manage strict evaluation frameworks and feedback loops to maintain system quality under stress.

Qualifications:

 Bachelor’s or Master’s degree in Computer Science, AI, ML, or a related field.

 Proven expertise in Python, system design, and scalable AI/ML architecture.

 Deep knowledge of NLP, Computer Vision, and Deep Learning models.

 Hands-on experience with Docker, Kubernetes, MLOps, and major cloud platforms (AWS, GCP, or Azure).