Machine Learning Engineer

About UsWe're a small but ambitious startup revolutionizing the e-commerce landscape with cutting-edge AI solutions. Our mission is to empower sellers with the tools and insights they need to thrive in the competitive online marketplace.We’re building a suite of AI-powered products and intelligent AI agents designed to streamline advertising, automate research, optimize listings, boost sales, and drive growth for businesses of all sizes.The Role: Senior Machine Learning Engineer (AI/ML & LLMs – E-Commerce Ads)We’re looking for a Senior Machine Learning Engineer to join our team and play a key role in developing the intelligence behind our AI-driven e-commerce platform.In this role, you’ll be responsible for designing, building, training, optimizing, and deploying machine learning and LLM-based models that power ad targeting, recommendation systems, personalization engines, performance prediction, and autonomous AI agents.You’ll own end-to-end ML pipelines — from data ingestion and feature engineering to model development, evaluation, and deployment — while also working hands-on with large language models to build intelligent workflows, tools, and automation.Responsibilities- ML & AI Model Development:Build, train, evaluate, and optimize ML models for ad performance prediction, personalization, targeting, and campaign optimization. - Experiment with classical ML and modern deep learning architectures to maximize performance. - LLM Development & Integration:Fine-tune, prompt-engineer, or build applications using large language models (e.g., OpenAI GPT-4, Claude, LLaMA). - Build intelligent agent workflows using LLMs for research automation, ad copy generation, optimization strategies, and seller assistance. - Integrate LLMs with internal data pipelines and APIs to deliver context-aware insights. - Data Pipelines & Feature Engineering:Design and implement scalable data pipelines for training and inference. - Process structured and unstructured e-commerce ad data for ML and LLM applications. - Model Deployment & Infrastructure:Deploy ML and LLM models to production using containerization, inference APIs, or orchestration frameworks. - Collaborate with backend teams to ensure seamless interaction between AI systems and product interfaces. - Experimentation & Evaluation:Design and run experiments (e.g., A/B testing) to evaluate and iterate on models. - Monitor model performance post-deployment and implement retraining or optimization strategies. - Architecture & Scalability:Contribute to the design of AI infrastructure supporting rapid experimentation and reliable deployment at scale. - Research & Innovation:Stay current on the latest advancements in ML, LLMs, and agentic AI systems. - Propose and prototype new capabilities to strengthen our product’s intelligence.Qualifications- Experience:3+ years of professional experience as a Machine Learning Engineer or similar role. - Proven experience building and deploying ML models and/or LLM-based solutions into production. - Technical Skills:Proficiency in Python and ML/AI frameworks like PyTorch, TensorFlow, or scikit-learn. - Strong understanding of ML algorithms, model evaluation, feature engineering, and MLOps best practices. - Experience working with and deploying LLMs (e.g., OpenAI GPT-4, Claude, LLaMA, or similar). - Familiarity with prompt engineering, fine-tuning, RAG (retrieval-augmented generation), and agent frameworks. - Experience with cloud platforms like Google Cloud Platform, Amazon Web Services, or Microsoft Azure. - Experience with containerization and model serving (e.g., Docker, Kubernetes, TensorFlow Serving, FastAPI). - Applied AI Experience:Strong background in supervised/unsupervised learning, predictive modeling, and experimentation. - Experience with recommender systems, ad optimization models, or marketing intelligence. - Familiarity with LLM integrations in production systems is a big plus. - Soft Skills:Strong problem-solving abilities and ownership mindset. - Excellent communication and collaboration skills. - Comfortable in a fast-moving startup environment.Bonus Points- Experience applying LLMs to real-world product use cases in e-commerce or marketing. - Knowledge of agentic AI architectures and multi-model orchestration. - Experience contributing to open-source ML/LLM projects. - Familiarity with backend/frontend systems to integrate AI into customer experiences. - Domain experience with e-commerce platforms (e.g., Amazon Seller Central).Why Join Us- Build AI that directly impacts thousands of e-commerce businesses. - Work on both ML and LLM innovation at the frontier of applied AI. - Own your work end-to-end in a lean, ambitious team. - Flexible work culture, high autonomy, and the chance to shape the future of our platform.