Job Description
KAYGEN is an emerging leader in providing top talent for technology-based staffing services. We specialize in providing high-volume contingent staffing, direct hire staffing and project-based solutions to companies worldwide ranging from startups to Fortune 500 and Managed Service Providers (MSP) across a wide variety of industries.
Title: Machine Learning / AI Contractor
Duration: Through 4/16/27
Location: Jersey City, NJ
Responsibilities:
- Design and ship production pricing agents on NEO, owning them from prototype through production, as part of the firm's federated portfolio of production agents.
- Build retrieval that holds up in production: Graph RAG combining knowledge-graph traversal over products, rate cards, clients, and pricing policy with vector search, plus chunking, ranking, and grounding strategies that keep price explanations accurate and auditable.
- Design agent memory: episodic and semantic memory organized as memory nodes, with recall, summarization, and decay policies tuned per use case, so an agent remembers the history of a negotiation without leaking it across clients.
- Own organizational context management — assembling entitlement-, lineage-, and tenant-aware context so each agent reasons over only the pricing data it is allowed to see.
- Build and productionize ML model training pipelines for price optimization, elasticity, win-probability, and deal-scoring models using MLOps best practices, including feature engineering over billing, transaction, and deal history data on Databricks.
- Build batch and online inference for those models, meeting the latency a seller conversation requires while keeping every scored recommendation reproducible.
- Own model validation in a revenue-sensitive setting: back-testing against realized prices, challenger models, uplift and elasticity measurement, and monitoring for drift, margin erosion, and revenue leakage in production.
- Compose multi-agent workflows using A2A, and integrate tools and data through MCP servers (pricing engine, rate card store, CRM, billing and revenue data, Databricks, Snowflake, Kubernetes, Confluence, Bitbucket, Splunk).
- Build and run evals: task-level and end-to-end agent evaluations, regression suites, LLM-as-judge, numerical-correctness and explanation-faithfulness checks, and quality and safety gating before release.
- Produce the model documentation, test evidence, and controls the firm's model risk review requires for a model that influences client pricing, and keep that evidence current as models are retrained.
- Deploy and operate solutions on public cloud (AWS and/or Azure) with strong SDLC, security, resiliency, and observability practices.
- Partner with pricing, product, finance, and business partners across CIB and Payments to turn use cases into shipped, supported agents.
- MS in Computer Science, Statistics, Mathematics, Machine Learning, or related field (or equivalent experience).
- Hands-on experience building LLM-powered or agentic applications in production, including tracing, evaluations, and guardrails.
- Hands-on experience taking predictive or optimization models to production and keeping them healthy there, including validation, monitoring, and retraining.
- Practical RAG experience — retrieval quality, embeddings, and vector stores; Graph RAG a strong plus.
- Strong programming skills in Python, with deep knowledge of data structures, algorithms, machine learning, data mining, information retrieval, and statistics.
- Knowledge of Kubernetes (AWS EKS).
- Experience with training models in Databricks and SageMaker.
- Experience working with MLflow.
- Expert knowledge of at least one of: AWS, Azure, Kubernetes.
- Knowledge of data management and data model design; real-time processing using both SQL (e.g., Postgres) and NoSQL stores (e.g., OpenSearch, Redis).
- Excellent communication skills with the ability to partner effectively with senior technical and business stakeholders.
- Experience with pricing, revenue management, elasticity, or demand forecasting models in a production setting.
- Experience with mathematical optimization (linear and mixed-integer programming, e.g., OR-Tools or Gurobi) and with constrained recommendation problems.
- Experience with causal inference, uplift modelling, or experiment design where randomization is limited.
- Experience delivering models through model risk management or equivalent regulatory review.
- Experience working in the financial or payments domain at a large institution (Investment Banking, Markets, Securities Services, or adjacent), or with commercial card, treasury services, or billing and revenue systems.
- Experience with agent frameworks or runtimes, A2A, or MCP.
- Agent memory design (memory nodes, episodic/semantic memory) and organizational context management.
- Knowledge graphs and graph databases used for retrieval.
- Understanding of LLM fine-tuning and small language model inference.
- Ability to develop full-stack products using modern JavaScript/TypeScript frameworks (e.g., Next.js, Svelte) for agent UIs (AG-UI / NEO UI SDK).
- Knowledge of high-performance languages such as Go or Rust.
Rate: 60 - 75
At KAYGEN, people are at the heart of everything we do. We foster a diverse, inclusive, and employee-driven culture where every individual is valued, empowered, and encouraged to bring their authentic self to work. Our candidate-first approach means we are committed to understanding your career goals and connecting you with opportunities that align with your aspirations, skills, and potential. Whether you're taking the next step in your career or searching for your dream opportunity, KAYGEN is more than a staffing partner—we're a community dedicated to helping you grow, succeed, and thrive. Join us and discover a place where your talent is recognized, your ambitions are supported, and your future is built alongside a team that invests in your success every step of the way.
Our team of experienced staffing experts will work with you to find you the best opportunity. For more information, please visit us at www.kaygen.com.
Benefits:
- Free Healthcare Insurance
- 401(k) Retirement Plan
- Free Life Insurance
- Sick Time Off
- Mentorship Program
- Certifications
- Referrals
- Family and Wellness benefits
- Continuous Growth and Career Development
Numbers & Facts
| Location | Jersey City, NJ |
| Industry | Computer/IT Services |
| Salary | $60–$75 Per Hour |
| Company Size | 100 to 499 employees |
| Year Founded | 2003 |
| Website | http://www.kaygen.com |
Benefits
Paid Sick Days, Professional Development, 401K, Employee Referral Program, Flexible Spending Accounts, Employee Events, Life Insurance, Merchandise Discounts
About Company
Kaygen, an award-winning technology consulting and talent firm, assists organizations to achieve digital transformation. From structuring data to the Cloud and visualization, Kaygen leads the digital transformation of global clients.
Kaygen, from the Japanese word, kaizen, for continuous improvement, signifies how we continuously seek to bring expert tech talent to our client engagements to create a sustainable competitive advantage. However, there is more. Our company is diverse, and minority woman owned and operated by expert data technologists who have conceived and developed the very strategic technology initiatives that we now engage in for our clients with our talent.
Our core belief in diversity, complemented by the principles of kaizen, ensures we bring the best expert data talent to work transparently, collaboratively, and with the flexibility to ensure client success.
Visit http://www.kaygen.com/ for a solutions overview.
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