AI Lead

Beetexting; Hyderabad; On-site; INR 900,000 - 1,400,000; Full time

Job summary

Beetexting, a growth-stage SaaS company with a cutting-edge development center in Hyderabad, is seeking a Senior AI/ML leader to drive end-to-end AI/ML systems, including Generative AI, LLMs, and RAG.

You will architect scalable pipelines, lead model design and optimization, and mentor teams across product, data engineering, and security to deliver high-impact solutions. Location: Hyderabad, India, with a focus on scalable, responsible AI.

Qualifications

• 15+ years in AI/ML roles with 7–10 years in Generative AI/Deep Learning
• Hands-on coding and deployment in production environments (Python, C++, Java)
• Strong track record in leading AI/ML initiatives and teams
• Experience with large language models, multimodal models, and RAG systems
• Familiarity with end-to-end ML systems, from data engineering to deployment

Responsibilities

• Lead end-to-end development and deployment of cutting-edge AI/ML systems
• Architect scalable Retrieval-Augmented Generation pipelines and multi-agent frameworks
• Drive model design, training, evaluation, and production delivery
• Define best practices for prompt engineering, fine-tuning, and optimization
• Build robust MLOps pipelines and ensure secure, compliant deployments
• Mentor engineers and data scientists and collaborate with cross-functional teams

Skills

AI/ML architecture

Generative AI

Deep Learning

Python

Deployment & MLOps

Model optimization

Prompt engineering

Team leadership

Research & publications

Cloud platforms

Education

Master’s or PhD in AI/ML or related field

Tools

PyTorch

TensorFlow

MLflow

LangChain

NVIDIA NeMo

Job description

15+ years in AI/ML roles, 7+ years of experience in Generative AI and Deep Learning…

Join Beetexting – Revolutionizing Communication with Cutting-Edge Technology!

About Us:

Beetexting is a growth stage and VC-backed SaaS company headquartered in the USA with a cutting-edge development center in Hyderabad, India. We are on a mission to build next-gen software products that transform communication with AI. Our team thrives on innovation, passion, and a relentless pursuit of excellence. We are looking for code lovers who are excited to develop groundbreaking products and make a real impact in the market.

Why Join Beetexting?

• We are entrepreneurs. We’re resourceful and positive
• We are innovators. We obsess on helping our customer win.
• We are visionaries. We think deeply about the industry and think way, way ahead.
• We are beelievers. We’re humble. We believe in each other and support one another.
• We are givers. We think of others first.
• We are intentional. We plan.
• We are diligent. We measure outcomes and stay focused on the profitable.
• We are gritty. We execute and we never give up.

Key Responsibilities:

• Spearhead the end-to-end development, deployment, and continuous optimization of cutting-edge AI/ML systems—Generative AI, LLMs/MLLMs, RAG, autonomous agents, and custom MCP servers in production
• Architect and implement scalable Retrieval-Augmented Generation pipelines, multi-modal transformer systems, and autonomous multi-agent frameworks (LangChain, AutoGPT, BabyAGI, NVIDIA NeMo Agents)
• Lead deep-learning model design and delivery: ANN, CNN, RNN, LSTM/BiLSTM, attention-based Transformers (BERT, GPT, T5, Vision Transformers), GANs, VAEs, Diffusion models, and Mixture-of-Experts architectures
• Define and enforce best practices for prompt engineering, fine-tuning (LlamaIndex, Hugging Face), quantization (INT4, GGUF), pruning, distillation, and advanced inference optimizations
• Build and maintain robust MLOps pipelines: CI/CD (Git, Bitbucket, automated tests), model versioning (MLflow, Hugging Face Hub & LFS), Docker/GPU containerization, Kubernetes/OpenShift orchestration, Terraform infrastructure as code
• Design high-performance data engineering workflows: ETL optimization (Pandas, NumPy, Spark), real-time streaming (Kafka, RabbitMQ), and caching strategies (Redis)
• Ensure secure, compliant AI deployments by embedding Responsible AI principles (bias mitigation, transparency, privacy), governance frameworks, and regulatory controls.
• Monitor emerging research (self-supervised pre-training, federated learning, synthetic data, LLMOps) and integrate top innovations into production
• Collaborate closely with Product, DevOps, Data Engineering, and Security teams; mentor and guide engineers and data scientists in software engineering and model validation best practices

Required Qualifications:

• Education: Master’s or PhD in AI/ML, Computer Science (AI/ML specialization), Data Science, Mathematics, or related field
• Industry Experience: 15+ years in AI/ML roles, including 7–10 years hands-on in Generative AI and Deep Learning, plus 5+ years in senior or leadership positions
• Hands-On Coding & Deployment: Expert at architecting, writing, debugging, deploying, and optimizing production-grade AI/ML code in Python (primary), C++, R, Java/Spring Boot, with strong testing, code-review, and performance-profiling discipline
• Deep Learning & Generative AI Frameworks: Advanced usage of PyTorch, TensorFlow, ONNX, GGUF, Hugging Face Transformers & Diffusers; fine-tuning pipelines (LlamaIndex, custom scripts)
• Large Language & Multimodal Models: Production deployment of LLMs, Multimodal LLMs (vision-language models, cross-modal understanding), RAG systems, and custom MCP A2A servers; embedding management & vector search with Pinecone, Milvus, Chroma, Quadrant
• Advanced Model Optimization: Quantization, pruning, distillation, MoE routing, efficient inference strategies, prompt-engineering platforms (LangSmith, PromptFlow)
• Classical & Advanced ML: Proficiency in regression, decision trees, random forests, SVM; boosting (XGBoost, CatBoost, LightGBM); clustering (K-Means, DBSCAN, hierarchical); RL (Q-Learning, DDPG, PPO); statistical methods and optimization math
• Computer Vision & Document Processing: Expertise in OpenCV, PyMuPDF, python-docx/pptx, pytesseract for advanced text/image extraction and analysis
• Cloud & Infrastructure: GPU acceleration (CUDA, cuDNN); AWS (Bedrock, SageMaker), Azure AI Studio & GPU Containers, GCP (Vertex AI, Cloud Run), serverless AI, NVIDIA Triton Inference Server
• Backend & APIs: FastAPI, OpenAPI, Django REST Framework, Flask for building and scaling AI microservices
• Data Engineering & Storage: ETL pipelines, streaming, caching; relational (MySQL, Oracle SQL), NoSQL (MongoDB), vector DBs
• MLOps & Observability: MLflow, Kubeflow; Docker, Kubernetes, OpenShift; CI/CD (Git, Bitbucket); monitoring with Prometheus, Grafana, OpenTelemetry, Logstash, Kibana
• Security & Compliance: Secure coding, network security, and adherence to GDPR, HIPAA, GxP standards
• Industry Certifications & Research: Must hold at least one recognized AI/ML certification (e.g. AWS Certified Machine Learning – Specialty, Google Professional Machine Learning Engineer, Microsoft Certified: Azure AI Engineer Associate) and have published research papers in top-tier AI/ML conferences or journals (NeurIPS, ACM, arXiv, AAAI, JMLR).

Good to Have Skills:

• PhD-level publications and advanced certifications (Stanford AI, MIT, AWS, Google)
• Experience with federated learning, synthetic data generation, privacy-preserving ML (differential privacy, homomorphic encryption), and edge/in-device inference (TensorFlow Lite, CoreML)
• Familiarity with Responsible AI toolkits, model cards/DataCard’s, and AI risk management frameworks
• Significant open-source contributions to major AI/ML projects
• Proven success integrating AI in regulated industries (Texting/Messaging, pharma, healthcare, finance) Industries and disciplines.

Current Location (willingness to work from Hyderabad location *