Machine Learning Engineer

About Us

We'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.

AI-powered products and intelligent AI agents

The Role: Senior Machine Learning Engineer (AI/ML & LLMs E-Commerce Ads)

Senior Machine Learning Engineer

designing, building, training, optimizing, and deploying

data ingestion

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.