1

Manager Rlhf Jobs in New York (NOW HIRING)

Senior AI Engineer

New York, NY · On-site

$114K - $157K/yr

Apply reinforcement learning techniques (e.g., RLHF, RLAIF) to improve model alignment and task-specific performance * Architect and manage high-throughput, real-time data pipelines using Kafka

AI Engineering Lead

New York, NY · On-site

$250K - $340K/yr

You will be responsible for setting technical direction, managing execution, developing engineers ... Experience working with LLMs, transformer architectures, post-training methods (SFT, RLHF, DPO ...

... strategies metadata management and rerankin gEnsure accuracy relevance and performance of ... Experience finetuning LLMs LoRA PEFT RLHF concept sFamiliarity with evaluation frameworks for GenAI ...

Senior AI Engineer

New York, NY

$114K - $157K/yr

Apply reinforcement learning techniques (e.g., RLHF, RLAIF) to improve model alignment and task-specific performance * Architect and manage high-throughput, real-time data pipelines using Kafka

... strategies metadata management and reranki ngEnsure accuracy relevance and performance of ... RLHF conce ptsFamiliarity with evaluation frameworks for GenAI hallucination testing grounding ...

... strategies metadata management and rerankin gEnsure accuracy relevance and performance of ... Experience finetuning LLMs LoRA PEFT RLHF concept sFamiliarity with evaluation frameworks for GenAI ...

... strategies metadata management and rerankin gEnsure accuracy relevance and performance of ... Experience finetuning LLMs LoRA PEFT RLHF concept sFamiliarity with evaluation frameworks for GenAI ...

Job Category Software Engineering Job Details About Salesforce Salesforce is the #1 AI CRM, where ... DPO, RLHF) on curated trace data to name a few * Validate every optimization through A/B tests ...

... production. • Manage the model registry and lineage tracking to maintain governance and ... tuning, RLHF concepts • Agentic frameworks: ReAct, Tool-Augmented Agents, LangGraph, AutoGen ...

next page

Showing results 1-20

Manager Rlhf information

What are the most commonly searched types of Rlhf jobs in New York? The most popular types of Rlhf jobs in New York are:
What are popular job titles related to Manager Rlhf jobs in New York? For Manager Rlhf jobs in New York, the most frequently searched job titles are:
What job categories do people searching Manager Rlhf jobs in New York look for? The top searched job categories for Manager Rlhf jobs in New York are:
What cities in New York are hiring for Manager Rlhf jobs? Cities in New York with the most Manager Rlhf job openings:

Senior AI Engineer

Octus

New York, NY • On-site

$114K - $157K/yr

Full-time

Medical, Retirement, PTO

Posted 28 days ago


Job description

Octus
Octus is a leading global provider of credit intelligence, data, and analytics. Since 2013, tens of thousands of professionals across hedge fund, investment banking, management consulting, and law firm verticals have come to rely on Octus to make better, faster, and more confident decisions in pace with the fast-moving credit markets.
For more information, visit: https://octus.com/
Working at Octus
Octus hires growth-minded innovators and trailblazers across the globe to drive our business and culture. Our core values - Action Oriented, Customer First Mindset, Effective Team Players, and Driven to Excel - define an organizational ethos that's as high-performing as it is human. Among other perks, Octus employees enjoy competitive health benefits, matched 401k and pension plans, PTO, generous parental leave, gym subsidies, educational reimbursements for career development, recognition programs, pet-friendly offices (US only), and much more.
Role
As a Senior AI Engineer focused on CreditAI, our flagship GenAI product, you will own complex technical problems across the full AI stack - designing distributed systems, orchestrating multi-agent workflows, and ensuring production reliability at scale.
Responsibilities
  • Design and implement multi-agent and agentic orchestration frameworks using agent SDKs such as the Claude Agent SDK, Google ADK, or AWS AgentCore, incorporating tools, external data sources, memory, and state management
  • Build and maintain MCP servers and integrations to extend AI system capabilities with structured tool use and external context
  • Build and optimize RAG pipelines including embedding strategies, vector database, retrieval quality tuning, and cost-aware ingestion design
  • Integrate with managed LLM services across cloud providers to support diverse deployment and cost optimization strategies.
  • Fine-tune, optimize, and deploy open-source deep learning models for production use cases, leveraging GPU infrastructure for training and inference
  • Apply systems thinking to design and optimize AI and LLM systems, balancing quality, scalability, latency, cost, and operational complexity, while implementing efficiency improvements using model selection, prompt design, batching, caching, and retrieval strategies.
  • Design and implement automated evaluation frameworks to assess LLM system quality, accuracy, and performance across production workloads
  • Apply reinforcement learning techniques (e.g., RLHF, RLAIF) to improve model alignment and task-specific performance
  • Architect and manage high-throughput, real-time data pipelines using Kafka
  • Design, deploy, and scale production AI services on AWS (Batch, Lambda, ECS, S3, etc), applying modern containerization, CI/CD, and infrastructure-as-code practices
  • Implement comprehensive observability frameworks using Datadog - tracking token usage, pipeline latency, error rates, consumer lag, and model performance with actionable alerting
  • Identify and resolve production bottlenecks across distributed systems, including database query optimization, consumer scaling, and LLM throughput tuning
  • Apply strong problem-solving and critical thinking skills to break down complex, ambiguous requirements into clear, implementable technical components and system designs.
  • Conduct code reviews; contribute to team standards around reliability, testing, and operational excellence
  • Communicate progress, trade-offs, and outcomes to relevant stakeholders.
  • Continuously learn and adapt to advancements in NLP and Generative AI to ensure solutions remain innovative and effective.

Requirements
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
  • 5+ years of experience as an AI Engineer, Machine Learning Engineer, or applied AI practitioner, with a strong foundation in computer science and algorithms.
  • Deep Python expertise with a track record of shipping production systems at scale; strong software engineering practices including clean code, testing, code review, and CI/CD.
  • Hands-on experience designing, building, and deploying LLM-driven or GenAI applications, including multi-agent architectures and agentic workflows, with familiarity with vector databases, embeddings pipelines, or semantic search systems.
  • Hands-on experience designing and implementing automated evaluation frameworks for LLM systems
  • Solid understanding of machine learning and applied AI concepts, with the ability to take solutions from prototype to production and translate research ideas into scalable, real-world systems.
  • Experience with GPUs for model training or inference, including tuning and deploying open-source deep learning models in production; proficiency with PyTorch or TensorFlow for model development and fine-tuning.
  • Practical experience with cloud-based deployments and infrastructure tools (e.g., AWS, Docker, GitHub) and an understanding of modern DevOps practices, containerization, orchestration, and caching strategies.
  • Strong problem-solving and systems thinking, with the ability to balance trade-offs across model quality, scalability, inference latency, and cost.
  • Excellent communication and collaboration skills, with experience working closely with product managers, engineers, and domain experts to deliver actionable technical solutions.
  • Strong ownership and initiative, with the ability to independently drive projects from problem definition to delivery; a passion for learning and staying current with the rapidly evolving AI/ML landscape.

At Octus, we consider a range of factors in connection with compensation decisions, including experience, skills, location, and our business needs and limitations. As a result, compensation may vary within and across similar roles and positions. Please note that the salary range information below is a good faith estimate for this position and actual compensation for any individual may fall outside this range if warranted by the circumstances applicable to that individual. If we identify a role that would be suitable for a broader range of skills and experience such that we would consider hiring at multiple levels then the range listed below may reflect that breadth.
The salary range estimate for this position is $160,000 - $170,000.
The actual compensation will be at Octus' sole discretion and will be determined by the aforementioned and other relevant factors.
Equal Employment Opportunity
Octus is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, marital status, pregnancy, veteran status, or any other legally protected status. We strive to create an inclusive and diverse work environment where all individuals are valued, respected, and treated fairly. We believe that diversity enriches our workplace and enhances our ability to innovate and succeed.