AI Lead

Full Time
India
Posted 1 week ago

Beetexting, a beeline to deeper customer relationships.

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. 

Role Details:

Position: AI Lead

Location: Hyderabad, Telangana, India

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. 

How to Apply: 

If you are a passionate developer who loves coding and thrives in an innovative startup environment, apply now to join our journey in revolutionizing communication! 

Apply here or email to join@beetexting.com

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