Senior ML / AI Engineer

About Reacher :

We're the #1 TikTok Shop partner helping brands like Under Armour, Hanes, HeyDude, and Logitech scale their affiliate marketing. We've crossed 7 figures in ARR , and are rapidly scaling our team this year. Our vision is to become the Hubspot for creator marketing , powering brands and creators to connect and grow across all commerce platforms (Youtube Shopping, Instagram Shopping, Shopify, Amazon).

We're building key infrastructure for the creator economy and implementing AI with the world's largest brands and creators . Your work will directly impact users on day 1 —our user base depends on our product daily.

Your work will directly impact users on day 1. We have a highly responsive user base that depends on our product day in and day out.

What You'll Do

Own ML systems end-to-end : research, prototype, train, deploy, and iterate rapidly

Build multimodal ML systems for video, text, images, and audio at scale

Design and deploy LLM-powered applications using RAG and AI APIs

Develop content understanding and classification models for text and visual data

Build search and discovery systems using embeddings and semantic retrieval

Create audio analysis and processing pipelines

Build MLOps infrastructure —data pipelines, model serving, monitoring, and experiment tracking

Ideate ML / AI product features with product and customers

Leverage modern AI tools to accelerate development

Work directly with customers and translate vague requirements into shipped ML solutions

Ship fast and learn fast —high urgency environment

You're a Fit If

You have 4–7 years of ML engineering experience building and deploying models in production

You have strong Python and ML fundamentals and write clean, maintainable production code

You've built ML models end-to-end : data pipelines, training, serving, monitoring

You're experienced with modern ML frameworks (PyTorch, TensorFlow, scikit-learn)

You have production experience with LLMs and AI APIs (OpenAI, Anthropic, Hugging Face)

You can build ML systems across multiple domains —NLP, computer vision, and audio

You're product-minded and identify where ML can solve user problems and improve business metrics

You're comfortable with MLOps tools and cloud platforms (AWS or GCP)

You're resourceful and thrive in ambiguous environments

ML & AI-Specific Skills We Value

Core ML : Supervised / unsupervised learning, feature engineering, model evaluation, A / B testing

Deep Learning : Neural networks, transformers, CNNs, training and optimization

NLP / LLMs : RAG systems, prompt engineering, vector databases, fine-tuning, LangChain

Computer Vision : Image classification, object detection, OCR, visual content understanding, image embeddings

Audio / Speech : Audio classification, speech recognition (ASR), audio transcription

Search & Retrieval : Semantic search, embedding models, vector similarity, multimodal retrieval

MLOps : Model serving, monitoring, experiment tracking (MLflow, Weights & Biases), data pipelines

Cloud ML : AWS (SageMaker, Bedrock) or GCP (Vertex AI), model deployment, scalable inference

Bonus Points If

You've worked at an early-stage startup or been a first / early ML hire

You have experience building multimodal search systems or semantic retrieval at scale

You have experience with video understanding —extracting features, generating embeddings, or analyzing visual content

You've implemented feature stores or advanced MLOps infrastructure

You have experience with real-time inference and low-latency model serving

You have expertise in adversarial robustness and model safety testing

You've built hybrid RAG + fine-tuning systems

You have experience with multimodal models (vision + language, audio + text)

You're experienced with model optimization (quantization, distillation, pruning)

You have a track record of shipping ML-driven product features that moved key metrics

You've shipped side projects or contributed to open-source ML projects

Why Join Us

Post-revenue company solving real problems for real customers

Be the ML / AI leader —define our ML strategy and infrastructure as we scale

High autonomy and visibility —no boring tickets

Your models reach users within days, not months

Strong engineering-first culture

Shape both the product and the company

Work on diverse ML problems across video, language, and audio

Direct impact on product strategy —your ML ideas become features

When Applying :

Feel free to send a short note about something you've built and why this role excites you . GitHub / LinkedIn / resume is great, but we care more about how you think and build !