ML Engineer, Forward Deployed Job at Prior Labs

Forward Deployed ML Engineer

Triomics is building the agentic AI layer for oncology EHRs. Cancer hospitals sp...

Location

United States , New York

Salary:

170000.00 - 190000.00 USD / Year

Helpcare AI

Expiration Date

Until further notice

Requirements

2+ years building ML/AI systems in production
Built and deployed AI agents or multi-step LLM pipelines (not just single-call wrappers)
Strong Python
Practical LLM experience: prompt engineering, fine-tuning, RAG, evaluation design
Built evaluation frameworks for LLM based document extraction tasks (precision, recall, per-class analysis, error taxonomy)
Willingness to become a domain expert in oncology data
Comfortable owning customer-facing communication alongside technical delivery
Can operate in high-intensity delivery sprints and manage your own time across multiple workstreams

Job Responsibility

Design and build agentic extraction pipelines that process 500+ page patient charts and output structured JSON per customer data dictionaries
Own accuracy end-to-end: define evaluation datasets, run precision/recall analysis per variable, identify failure modes, and improve through agent architecture changes, prompt engineering, fine-tuning, or rule-based post-processing
Go deep into the clinical source data
Work with the clinical annotation team to build gold-standard datasets and resolve edge cases
Coordinate with customer data science and clinical teams to clarify dictionary definitions, review output quality, and close accuracy gaps
Coordinate with internal engineering and infrastructure teams to deploy, scale, and monitor pipelines in production
Deliver on customer timelines

Fulltime

Forward Deployed Engineer, Infrastructure Specialist

As a Forward Deployed Engineer, Infrastructure Specialist you will lead the end-...

Location

United States , San Francisco

Salary:

150000.00 - 300000.00 USD / Year

Reducto

Expiration Date

Until further notice

Requirements

5+ years of hands-on experience operating production infrastructure, with meaningful time spent deploying software into environments you don't fully control
Comfortable with Python or similar languages, and exceptional at working across cloud platforms, container orchestration (e.g., Kubernetes), networking, and storage technologies
Communicate clearly with external engineers
Energized by being assigned to a customer problem and owning it end-to-end
Build your own tools on the fly to diagnose, experiment, and address reliability problems
Bring a quantitative, hands-on approach to system operations, automation, and continuous improvement

Job Responsibility

Leading end-to-end deployment of Reducto into customer environments including planning, configuration, testing, and rollout
Partnering with enterprise IT, security, and platform teams to assess their infrastructure, security posture, and data management practices, and designing deployment strategies tailored to their constraints
Understanding the hardware that power our in-house ML models so we can successfully deploy them onto customer infrastructure
Building monitoring, telemetry, and phone-home patterns that give us visibility into customer-controlled environments without compromising their security posture
Debugging and resolving customer-specific infrastructure issues end-to-end, like K8s misconfigurations and cloud IAM edge cases, minimizing customer downtime
Owning incident response for customer deployments with world-class operational excellence
Codifying what works into repeatable deployment patterns, runbooks, and automation — turning one-off customer work into infrastructure that scales across the next ten deployments

What we offer

Unlimited PTO
Lunch
Reimbursed Transportation
Health insurance covering medical, dental, and vision
Health and Wellness Budget up to $150/mo
Parental Leave

Fulltime

Forward Deployed Engineer

We are hiring Forward Deployed Engineers to configure, deploy, and evolve our ag...

Location

United States , New York

Salary:

140000.00 - 160000.00 USD / Year

Chat3D

Expiration Date

Until further notice

Requirements

Graduated from top engineering school or business/engineering dual-degree
Prior client-facing technical experience, ideally supporting enterprise implementations
Hands-on work with conversational AI, LLM prompting, applied ML models, or workflow-based configuration
Ability to debug state logic, model outputs, and configuration inconsistencies
SQL proficiency for analytics and performance investigation
Comfort with light scripting and structured configuration formats
Strong ability to reason about system constraints and edge cases
Ability to distinguish between local configuration work and product-level feature needs
Structured approach to experimentation and iteration
Clear and concise communication with both technical and non-technical stakeholders

Job Responsibility

Build and adapt screening flows based on customer jobs and requirements
Configure state prompts, tone parameters, voice selection, transitions, and conditional logic
Set up and maintain custom vocabularies for ASR when relevant
Prepare and run demos
support pilot implementations from start to finish
Analyze conversation transcripts and identify sources of errors or drift
Run isolated state tests for targeted debugging
Iterate rapidly on prompts and configurations to improve performance
Use SQL to investigate behavioral patterns, identify systemic issues, and validate improvements
Advise customers on screening design, personas, and best practices for AI-driven interviews

Fulltime

Forward Deployed Engineer

We’re looking for a Forward Deployed Engineer who wants to help shape the future...

Location

Sweden , Stockholm

Salary:

Not provided

Predli

Expiration Date

Until further notice

Requirements

Hold a degree in Machine Learning, Computer Science, Data Science, or a related field, with a solid understanding of core ML principles
Skilled in Python or TypeScript and familiar with frameworks such as PyTorch, TensorFlow, or Scikit-learn
Experienced with databases, APIs, and data pipelines
Familiar with MLOps concepts, automation, and cloud environments
Based in Stockholm and fluent in English

Job Responsibility

Design and build AI solutions that create real business value by applying pre-trained models in new and practical ways, especially within language models
Build and extend features in Predli Studio that enable teams to use AI in their daily work
Develop scalable APIs, backend services, and data pipelines for production AI systems
Work with cloud infrastructure (AWS, GCP, Azure) and container technologies such as Docker and Kubernetes
Collaborate with clients and non-technical stakeholders to turn ideas into working solutions
Explore new AI tools and frameworks through internal projects and bring the most useful ones into production
Participate in knowledge sharing and code reviews to strengthen how we build as a team

What we offer

Be part of a tight-knit team where your ideas matter and your work has visible impact
Work across client projects, product development, and applied research
Contribute to Predli Studio and help shape how it evolves
Take part in internal R&D initiatives exploring new tools, workflows, and models
Collaborate across a global team with flexible ways of working
Competitive compensation and room to grow in the role

Forward Deployed Engineer

As a Forward Deployed Engineer (FDE) at LanceDB, part of the Engineering organiz...

Location

United States , San Francisco

Salary:

180000.00 - 250000.00 USD / Year

LanceDB

Expiration Date

Until further notice

Requirements

At least 2 years of experience in a technical field or forward deployed engineering role
Ability and willingness to be on-site at customers daily
Proven experience building, deploying, or operating distributed, cloud-native databases or data platforms in production
Strong proficiency in Rust and Python, with a demonstrated ability to write performant, maintainable systems code
Hands-on familiarity with data infrastructure technologies such as Apache Spark, Ray, or similar distributed compute and data processing frameworks
Experience integrating databases with batch and streaming data pipelines, ML workflows, or large-scale analytics systems
Demonstrated ability to contribute directly to core product codebases, not just customer-specific glue or scripts
Deep understanding of distributed systems concepts including sharding, replication, consistency, concurrency, and failure handling
Strong customer-facing skills, with the ability to work directly with engineers, architects, and technical leaders to drive solutions from concept to production

Job Responsibility

Lead on-site and remote technical deployments of LanceDB with enterprise and strategic customers, including architecture design, benchmarking, performance tuning, and operational hardening
Write and maintain production-grade code in Rust and Python for customer integrations, SDK enhancements, ingestion pipelines, and internal tooling
Contribute code upstream to LanceDB’s core repositories, including bug fixes, performance improvements, new features, and architectural refinements informed by customer use cases
Capture, distill, and communicate structured product feedback from customer engagements to product and core engineering teams, influencing roadmap and design decisions
Integrate LanceDB into existing data and AI infrastructure stacks, including Spark, Ray, and similar distributed processing frameworks
Diagnose and resolve complex issues involving distributed systems, cloud object storage, concurrency, and large-scale data movement
Partner closely with product, core engineering, and GTM teams to ensure customer requirements translate into generalizable, reusable platform capabilities
Deliver technical deep dives, workshops, and proofs-of-concept for engineers and architects at customer organizations

What we offer

Medical, dental, vision, and life insurance
401(k) retirement plan
Flexible Spending Accounts (FSA) and Health Savings Accounts (HSA)
Commuter benefits
Generous paid time off
Offers Equity
Offers Commission

Fulltime

Member of Technical Staff - Forward Deployed Engineer

You will work directly on customer engagements that generate revenue. This is ha...

Location

United States , San Francisco, Boston

Salary:

Not provided

Liquid AI

Expiration Date

Until further notice

Requirements

Hands-on fine-tuning experience with modern LLMs (last 12-18 months): LoRA, PEFT, DPO, instruction tuning, or similar
Strong ML fundamentals: you understand how models learn, fail, and improve
Experience generating or curating training data to address model gaps
Autonomous coding and debugging skills in Python and PyTorch
Proficiency with open-source ML ecosystem (Hugging Face transformers, datasets, accelerate)
Fine-tunes models: You have hands-on experience with techniques like LoRA, PEFT, DPO, instruction tuning, or RLHF. You've written training loops, not just API calls
Works with modern architectures: Your experience includes models released in the last 12-18 months (Llama 3.x, Mistral, Gemma, Qwen, etc.), not just BERT or classical ML
Generates and curates data: You've created synthetic training data to address specific model failure modes. You understand how data quality drives model performance
Debugs methodically: When a model underperforms, you diagnose whether it's a data problem, architecture problem, or training problem, and you fix it
Ships to customers: You can translate ambiguous customer requirements into concrete technical specs and deliver against quality metrics

Job Responsibility

Fine-tune LFMs on customer data to hit quality and latency targets for on-device and edge deployments
Generate and curate training data to address specific model failure modes
Run experiments, track metrics, and iterate until customer success criteria are met
Translate ambiguous customer requirements into concrete technical specifications
Provide analytics to commercial teams for contract structuring and pricing
Work across text, vision, and audio modalities as customer needs require

What we offer

Competitive base salary with equity in a unicorn-stage company
We pay 100% of medical, dental, and vision premiums for employees and dependents
401(k) matching up to 4% of base pay
Unlimited PTO plus company-wide Refill Days throughout the year

Fulltime

Senior Software Engineer, Forward Deployed

As a Senior Software Engineer, Forward Deployed Engineer (FDE) you'll work direc...

Location

United States , New York

Salary:

180000.00 - 264000.00 USD / Year

Invisible Technologies

Expiration Date

Until further notice

Requirements

7+ years of software engineering experience, including significant time spent building data, ML, or backend systems
Deep proficiency in Python with hands-on experience using Hugging Face, LangChain, OpenAI, Pinecone, and related ecosystems
Skilled in full-stack and API-based deployment patterns, including Docker, FastAPI, Kubernetes, and cloud environments (GCP, AWS)
Experienced with workflow orchestration libraries, pub/sub systems (Kafka), and schema governance
Expertise in data governance and operations, including Unity Catalog and policy management, cluster/job orchestration, data contracts and quality enforcement, Delta/ETL pipelines, and replay processes
Strong product and distributed systems skills — you understand business needs and how to translate them into technical architecture
Experience building usable systems from messy data and ambiguous requirements
Excellent communication and client-facing skills
you’ve led conversations with technical and non-technical stakeholders alike
Proven experience owning projects from scoping through deployment in ambiguous, high-stakes environments

Job Responsibility

Collaborate with delivery leaders to scope technical solutions to operational problems
Identify workflow optimizations through deep engagement with customer problems and work to build into a stable and scalable solution
Design and implement AI-powered workflows using LLMs, embedding models, retrieval systems, and automation tools
Translate messy real-world constraints (e.g., inconsistent data, latency requirements) into elegant engineering solutions
Iterate quickly based on real-time feedback from operators and clients
Build reusable tooling and infrastructure that accelerates future deployments

Fulltime

Principal Backend Engineer, Forward Deployed

As a Principal Forward Deployed Engineer (FDE) at Invisible, you'll lead high-im...

Location

United States , Austin; New York; San Francisco Bay Area; Washington DC–Baltimore

Salary:

225000.00 - 370000.00 USD / Year

Invisible Technologies

Expiration Date

Until further notice

Requirements

12+ years of software engineering experience, including significant time spent building data, ML, or backend systems
Deep proficiency in Python with hands-on experience using Hugging Face, LangChain, OpenAI, Pinecone, and related ecosystems
Skilled in full-stack and API-based deployment patterns, including Docker, FastAPI, Kubernetes, and cloud environments (GCP, AWS)
Experienced with workflow orchestration libraries, pub/sub systems (Kafka), and schema governance
Expertise in data governance and operations, including Unity Catalog and policy management, cluster/job orchestration, data contracts and quality enforcement, Delta/ETL pipelines, and replay processes
Strong product and system design instincts — you understand business needs and how to translate them into technical architecture
Experience building usable systems from messy data and ambiguous requirements
Excellent communication and client-facing skills
you’ve led conversations with technical and non-technical stakeholders alike
Proven experience owning projects from scoping through deployment in ambiguous, high-stakes environments

Job Responsibility

Partner with delivery and executive stakeholders to scope, design, and lead implementation of AI-driven solutions
Identify transformational opportunities in messy, ambiguous workflows and turn them into repeatable systems
Lead architecture design and trade-off discussions across performance, scalability, cost, and reliability
Own projects from first discovery call through full deployment — including client-facing delivery, internal coordination, and post-launch iteration
Build shared infrastructure, reusable components, and internal playbooks to level-up the team
Coach and mentor mid-level engineers and help shape the culture of forward-deployed AI engineering at Invisible

What we offer

bonus
equity

Fulltime

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ML Engineer, Forward Deployed

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