Senior ML/AI Engineer, Agentic Intelligence
New York City, New York, United States
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
Visa sponsorship available
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What you’ll work on
Full postingYou'll build and deploy the intelligent systems at the core of Merciv.
Design, build, and deploy ML models for demand forecasting, time series prediction, consumer sentiment analysis, and anomaly detection at enterprise scale
You'll work at the intersection of cutting-edge research and real enterprise deployment, building systems that generate tens of millions in value for clients.
From the employer’s posting
The Role You'll build and deploy the intelligent systems at the core of Merciv. Our platform doesn't just surface insights — it reasons, forecasts, and acts autonomously across complex enterprise data landscapes. You'll develop the models and agentic architectures that power demand forecasting, consumer intelligence, competitive analysis, and autonomous decision-making for the world's largest retailers. This is applied AI at its most impactful. You'll work at the intersection of cutting-edge research and real enterprise deployment, building systems that generate tens of millions in value for clients.
What You'll Do Design, build, and deploy ML models for demand forecasting, time series prediction, consumer sentiment analysis, and anomaly detection at enterprise scale Develop and iterate on Merciv's agentic AI architecture — building systems that reason across heterogeneous data sources and take autonomous action
You'll build and deploy the intelligent systems at the core of Merciv. Our platform doesn't just surface insights — it reasons, forecasts, and acts autonomously across complex enterprise data landscapes. You'll develop the models and agentic architectures that power demand forecasting, consumer intelligence, competitive analysis, and autonomous decision-making for the world's largest retailers. This is applied AI at its most impactful. You'll work at the intersection of cutting-edge research and real enterprise deployment, building systems that generate tens of millions in value for clients. What You'll Do
Education & alternatives
- You have 5+ years of applied ML/AI experience with models deployed in production - You have an M.S. or Ph.D. in CS, Machine Learning, Statistics, or equivalent practical experience - You're deeply proficient in Python with hands-on experience in PyTorch, TensorFlow, or scikit-learn
Tools in this posting
- Python
- PyTorch
- TensorFlow
- scikit-learn
Source — Tool mentions in context
- You have an M.S. or Ph.D. in CS, Machine Learning, Statistics, or equivalent practical experience - You're deeply proficient in Python with hands-on experience in PyTorch, TensorFlow, or scikit-learn - You have a strong background in statistical analysis, predictive modeling, and time series forecasting
About Merciv
Merciv is building the intelligence layer for enterprise commerce.
In the employer’s words · Read in context
Job description
About Merciv
Merciv is building the intelligence layer for enterprise commerce. We connect an organization's entire data landscape — internal systems, social signals, industry reports, consumer behavior — and surface the insights and automated workflows that used to take analysts weeks.
We raised $14M in seed funding, spent two years in stealth building the right thing, and we're now launching publicly. Our platform already drives 8-figure gross margin improvements for some of the world's largest retailers.
We're a lean, high-ownership team. If you want to see your work matter immediately, this is it.
The Role
You'll build and deploy the intelligent systems at the core of Merciv. Our platform doesn't just surface insights — it reasons, forecasts, and acts autonomously across complex enterprise data landscapes. You'll develop the models and agentic architectures that power demand forecasting, consumer intelligence, competitive analysis, and autonomous decision-making for the world's largest retailers.
This is applied AI at its most impactful. You'll work at the intersection of cutting-edge research and real enterprise deployment, building systems that generate tens of millions in value for clients.
What You'll Do
Design, build, and deploy ML models for demand forecasting, time series prediction, consumer sentiment analysis, and anomaly detection at enterprise scale
Develop and iterate on Merciv's agentic AI architecture — building systems that reason across heterogeneous data sources and take autonomous action
Build and maintain robust ML pipelines: data preprocessing, feature engineering, model training, evaluation, and production deployment
Architect RAG systems and LLM integrations that power Merciv's natural language interfaces and autonomous workflows
Collaborate with backend engineers to ensure models are production-grade — optimized for latency, reliability, and scale
Own model performance end-to-end: monitoring, retraining, and continuous improvement in production
Stay at the frontier of AI research and bring relevant innovations into the platform
You May Be a Good Fit If
You have 5+ years of applied ML/AI experience with models deployed in production
You have an M.S. or Ph.D. in CS, Machine Learning, Statistics, or equivalent practical experience
You're deeply proficient in Python with hands-on experience in PyTorch, TensorFlow, or scikit-learn
You have a strong background in statistical analysis, predictive modeling, and time series forecasting
You've worked on agentic AI systems, multi-agent orchestration, NLP, LLMs, and RAG architectures
You care about model interpretability and building systems enterprise users can actually trust
Former technical founders are encouraged to apply — we care more about what you've built than how long you've been building
Bonus points for:
Background in retail, supply chain, or demand forecasting
Experience with graph neural networks or knowledge graphs
Familiarity with MLOps platforms and model serving infrastructure
Open-source contributions or published research
How We're Different
Most AI platforms bolt intelligence onto existing workflows. We're building the intelligence layer from scratch — connecting every data source an enterprise touches and making it actionable in real time. Our agentic infrastructure doesn't just surface insights; it acts on them. That's a harder problem, and it's the one we're solving.
Why Merciv
Our platform drives 8-figure gross margin improvements for the world's largest retailers — you'll see real impact fast
Hard technical problems at the intersection of agentic AI, distributed systems, and enterprise data
Small team, massive surface area — you own what you build
Competitive salary, meaningful equity, health/dental/vision, 401k, home office stipend, flexible PTO
A culture built on craft, intellectual honesty, and real human connection
Interview Process
Application reviewed by a human
Intro call with our recruiting team
Technical conversation with an engineering lead
On-site — meet the team, work through a real problem
We Encourage You to Apply
Strong candidates don't always meet every qualification listed. If you're excited about this problem space and have the ML fundamentals, we'd rather talk to you than not. We're building a diverse team on purpose — different perspectives make the product and the company better.
Logistics
On-site in NYC, 3-5 days/week
Visa sponsorship available
Applications reviewed on a rolling basis
Merciv is building the future of autonomous commerce. We're committed to assembling a diverse team of builders who want to revolutionize how the world does business.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
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Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
New York City, New York, United States
- Technical conversation with an engineering lead - On-site — meet the team, work through a real problem We Encourage You to Apply
More source context
Logistics - On-site in NYC, 3-5 days/week - Visa sponsorship available
- Work authorization
- On-site in NYC, 3-5 days/week - Visa sponsorship available - Applications reviewed on a rolling basis
- Status in our records
- Active
- First seen by us
- Jun 2, 2026
- Recorded sightings
- 51
- Last seen by us
- Oct 7, 2026
- Employer says posted
- Mar 2, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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