Senior Marketing Manager – AI/ML Services & SaaS (Lead Funnels & Growth),(Custom Apps & AI white labels solutions)

Position: Senior Marketing Manager
Experience: 6–10 years
Location: Onsite
Employment Type: Full-time

We’re looking for a Senior Marketing Manager who can build marketing from the
ground up, drive demand generation, and establish our brand as a leader in both
custom Apps, AI/ML services and white-label AI solutions.

Key Responsibilities:

Marketing Strategy & Leadership
• Define and execute end-to-end marketing strategy for both the services
business and product business.
• Create brand positioning, messaging, and GTM (Go-to-Market) plans for
different industries (Finance, Healthcare, Retail, Legal, etc.).
• Build and manage the entire marketing funnel from scratch (awareness →
engagement → conversion → retention).
• Align closely with Sales, SDRs, and Product teams to ensure consistency and
ROI.

Lead Generation & Funnels
• Design and execute inbound and outbound lead funnels.
• Manage digital marketing campaigns across LinkedIn, Google Ads, SEO, and
industry events.
• Implement lead nurturing strategies (email marketing, webinars, content
campaigns).
• Support SDRs with playbooks, case studies, and targeted campaign content.

AI/ML-Enabled Marketing
• Leverage AI tools (ChatGPT, Jasper, Copy.ai, Surfer SEO, MidJourney) for faster
campaign execution.
• Create personalized content & email campaigns using LLM-powered tools.
• Deploy chatbots and AI-driven assistants to qualify and engage leads.
• Understand basic AI/ML concepts (LLMs, RAG, SLM fine-tuning) to
communicate ideas effectively with both clients and engineers.

Content & Brand Development
• Oversee creation of blogs, whitepapers, case studies, investor decks, and
demo videos.
• Build brand authority through thought leadership campaigns (LinkedIn
posts, webinars, events).
• Manage social media presence with data-driven strategies.
• Ensure consistent branding across services and product marketing.

Analytics & Optimization
• Define and track marketing KPIs (MQLs, SQLs, CAC, LTV, ROAS).
• Use analytics tools (Google Analytics, HubSpot, SEMrush, Ahrefs) to measure
and improve performance.
• Report campaign effectiveness to leadership and optimize based on data
insights.

Team & Collaboration
• Can Lead and mentor a team.
• Collaborate with engineering & AI teams to align technical offerings with
market messaging.
• Manage external agencies and partners for ads, PR, and events(If required).

Required Qualifications
• Bachelor’s/Master’s degree in Marketing, Business, or related field.
• 6–10 years of experience in B2B Marketing (preferably SaaS/AI/Tech).
• Proven track record of building marketing from scratch in a startup/scale
up environment.
• Strong understanding of digital marketing channels (SEO, SEM, Social, Email,
Events).
• Hands-on experience with CRM & marketing automation tools (HubSpot
and Zoho).
• Familiarity with AI-powered marketing tools (Jasper, ChatGPT, Copy.ai,
Surfer SEO, Canva AI).
• Excellent leadership, communication, and presentation skills.
• Ability to balance strategy with execution — hands-on when needed.

Nice-to-Have Skills
• Exposure to white-label SaaS marketing or enterprise AI/ML solutions.
• Experience with event marketing (AI/Tech conferences, webinars, expos).
• Knowledge of account-based marketing (ABM) for enterprise clients.
• Basic understanding of AI Terms.

What We Offer
• A chance to lead marketing from the ground up across two fast-growing
AI businesses.
• Work directly with founders, engineers, and sales leaders on cutting-edge
AI/ML solutions.
• Competitive compensation + performance-based incentives.
• Growth opportunity to move into Head of Marketing/CMO role.

AI/ML Engineer  – LLMs, RAG, Reinforcement Learning 
Experience: Not required
Employment Type: Full-time
Studies : Mtech or PhD

About the Role
We are building enterprise-grade AI/ML solutions including SLMs, LLMs, RAG-based
knowledge systems, reinforcement learning, and agentic AI,

As a Mid-level AI/ML Engineer, you will design, train, and deploy machine learning models,
collaborate with our product and engineering teams, and ensure scalable integration of AI
models into real-world applications.

This role is ideal for someone with a strong hands-on background in NLP, deep learning,
and reinforcement learning, who is eager to grow by working on cutting-edge AI projects
at scale.

Key Responsibilities
• Design, train, and fine-tune ML/DL models (with focus on transformers, SLMs,
LLMs, and recommender systems).
• Implement RAG pipelines using vector databases (Pinecone, Weaviate, FAISS) and
frameworks like LangChain or LlamaIndex.
• Contribute to LLM fine-tuning using LoRA, QLoRA, and PEFT techniques.
• Work on reinforcement learning (RL/RLHF) for optimizing LLM responses.
• Build data preprocessing pipelines for structured and unstructured datasets.
• Collaborate with backend engineers to expose models as APIs using FastAPI/Flask.
• Ensure scalable deployment using Docker, Kubernetes, AWS/GCP/Azure ML
services.
• Monitor and optimize model performance (latency, accuracy, hallucination rates).
• Use MLflow / Weights & Biases for experiment tracking and versioning.
• Stay updated with the latest research papers and open-source tools in AI/ML.
• Contribute to code reviews, technical documentation, and best practices.

Required Skills & Qualifications
• Strong in Python (NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow).
• Solid understanding of NLP and LLM architectures (Transformers, BERT, GPT,
LLaMA, Mistral).
• Practical experience with vector databases (Pinecone, or FAISS or PgVector).
• Basic Knowledge with MLOps tools – Docker, Kubernetes, MLflow, CI/CD.
• Basic Knowledge of cloud platforms (AWS Sagemaker, GCP Vertex AI, or Azure
ML).
• Good grasp of linear algebra, probability, statistics, optimization.
• Strong debugging, problem-solving, and analytical skills.
• Familiarity with Agile methodologies (Scrum, Jira, Git).

Nice-to-Have Skills
• Experience with RLHF pipelines.
• Open-source contributions in AI/ML.

Soft Skills
• Strong communication – able to explain AI concepts to technical & non-technical
stakeholders.
• Collaborative – works well with product, design, and engineering teams.
• Growth mindset – eager to learn new AI techniques and experiment.
• Accountability – able to deliver end-to-end model pipelines with minimal
supervision.
• Can works in a team.

What We Offer
• Work on cutting-edge AI projects with real-world enterprise impact.
• Exposure to LLMs, reinforcement learning, and agentic AI.
• Collaborative Startup & Service culture with room for fast growth.
• Competitive compensation + performance-based incentives.