Reacher
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 !
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 !