About Parloa

Parloa’s mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates, Parloans are shaping the foundation of a new era in customer experience, one where customer support is no longer transactions, but meaningful exchanges. It is not just a vision; Parloa has powered over ONE BILLION interactions between global enterprise brands and their customers, with companies like IKEA and Booking.com already deploying Parloa at scale. 

About the role:

As a Principal Applied Scientist at Parloa, you will define and drive our applied AI strategy across AI agents and Generative AI.

This is a highly hands-on and high-impact role at the intersection of research and production. You will explore, validate, and scale approaches that directly shape our product, from model evaluation and routing to agent behavior, memory, and context engineering, while defining how these systems should be measured, benchmarked, and improved across the industry.

Beyond execution, you will act as a technical leader: identifying opportunities, setting direction, and building the foundations of applied science at Parloa.

Areas of ownership:

• Define and lead applied AI initiatives across agent systems, LLM evaluation, and model optimization
• Own ambiguous problem spaces end-to-end: from framing and experimentation to production impact
• Design and implement evaluation & benchmarking frameworks, leveraging and challenging industry standards — and where needed, defining new ones
• Drive innovation in agentic systems, including topics like routing, memory, and context engineering
• Prototype and validate new approaches (e.g., model combinations, fine-tuning strategies, or open-weight models)
• Translate research into production-ready solutions, working closely with engineering teams
• Act as a technical authority and multiplier, mentoring others and shaping best practices
• Establish and lead the Applied Science guild, fostering knowledge sharing and raising the bar across teams
• Influence product and technical strategy, identifying where applied science can unlock the most value

Who you are:

• 12+ years of experience in Applied Machine Learning, Applied Science, or a related field, with a proven track record of delivering ML/AI systems in production
• Experience with agent-based systems or multi-step LLM workflows
• Strong recent experience working with LLMs and Generative AI systems, ideally in production environments
• Demonstrated ability to own and drive ambiguous problem spaces end-to-end—from problem framing to measurable impact
• Deep understanding of evaluation methodologies, benchmarking, and model performance analysis, including human-in-the-loop approaches
• Hands-on technical skills, with the ability to prototype, experiment, and ship solutions in collaboration with engineering teams
• Experience working on production systems, balancing speed, quality, and scalability
• Proven technical leadership and influence, with experience shaping direction, mentoring others, or driving cross-team initiatives
• Ability to operate at both strategic and execution levels, connecting long-term vision with day-to-day decisions
• Strong communication skills, with the ability to clearly articulate ideas and influence technical and non-technical stakeholders
• Evidence of broader impact (e.g., published work, open-source contributions, internal initiatives, or industry influence) is a plus

We know that great candidates don’t always meet every single requirement. If you’re excited about this role and believe you could make an impact, we encourage you to apply, even if your experience doesn’t perfectly match every qualification.

Nice to have

• Familiarity with model routing, fine-tuning, or open-weight models
• Background in human-in-the-loop evaluation or annotation systems
• Contributions to public research, blogs, or open-source projects

Our recruiting process:

Talent Acquisition → Technical Peer Interview → 360° Technical Interview Loop → Bar Raiser

Why Parloa?

We’re at the beginning of a new era in customer experience, one where AI doesn’t just respond, but understands, reasons, and takes action. We’re building agentic AI that enterprises trust with their most important customer moments: complex questions, high volumes, real stakes. When millions of people reach out to a brand, those interactions aren’t just support tickets; they’re defining experiences. We’re here to raise the standard: making every conversation seamless, intelligent, and genuinely helpful. If you care about shaping how businesses and customers connect at scale—and want your work to matter in real, everyday moments—this is where you do it.

At Parloa, ownership isn’t a buzzword; it means being accountable for outcomes, not just tasks. We operate in a category that’s evolving fast, where the bar is high, and the problems are complex. We hire people who think in solutions, communicate with clarity, and follow through. People who are comfortable making decisions, taking responsibility, and raising the standard for themselves and those around them.

We’ve grown beyond the earliest startup phase, but we’ve kept the intensity: fast execution, direct feedback, and a strong expectation to contribute meaningfully from day one.

Backed by leading global investors like General Catalyst, EQT Ventures, and Altimeter Capital, we’re scaling with a clear ambition: to become the global category leader in enterprise-grade conversational AI.

Locations:

• Europe: Paris / UK / Germany / Remote (EU)

About the role

We are looking for a scientifically credentialed strategist to lead the post-sales journey for our pharmaceutical partners. In this role, you will be the bridge between our cutting-edge foundational models and the R&D pipelines of the world’s leading biopharma companies.

You will use your deep expertise in machine learning and computational biology to build credibility with stakeholders, identify new opportunities for model application within their pipelines, and translate customer feedback into our product roadmap.

What you'll be doing

As our Applied AI Scientist (Pharma Partnerships) you are the primary architect of value for our most critical pharmaceutical partnerships. You will operate at the intersection of computational biology, ML and commercial scale across two strategic domains:

1. Partnership Value Realisation & Growth

• Post-Signature Leadership: Orchestrate the partner journey immediately following contract execution. You will act as the Project Manager for the deployment, ensuring seamless onboarding and integration of our foundational models.
• Scientific & technical thought-leadership: Consult with client R&D teams (ranging from bench scientists and data science teams to Heads of R&D) to diagnose their specific therapeutic challenges. Identify key use cases where our AI foundation models can unlock high value to our customers research and therapeutic priorities.
• Commercial Adoption & Growth: Proactively identify opportunities to expand the scope of the partnership. Leverage your understanding of the client’s pipeline to suggest new use cases, therapeutic areas, or departments where our technology can drive value.

2. Product Intelligence & Roadmap Influence

• Voice of the Customer: Synthesize technical feedback and performance metrics from the field. Translate complex biopharma user requirements into actionable technical specifications for our internal Research and Product teams. Identify high value opportunities to enrich our model capabilities and biology applications offering.
• Gap Analysis: Collaborate with our machine learning engineers to identify data modalities or functional gaps in our current offering, directly influencing future product iterations.

What you'll bring

The successful candidate will have a ‘team-first’ attitude; be independent, curious, and detail-oriented; thrive in a dynamic, fast-paced environment; and be fun to work with. We value individuals who bring deep domain expertise in computational biology, ML and pharmaceutical R&D alongside strong hands-on business development skills.

Scientific & Technical Credibility

• Educational Background: PhD in Computational Biology, Machine Learning, Bioinformatics, Genomics, or a related field is required.
• Domain Expertise: Deep understanding of the biopharma R&D value chain (target discovery to clinical trials). You understand the specific pain points of drug developers and are able to translate ambiguous biopharma use cases into rigorous ML applications.
• Technical Fluency:
• Deep experience in biological data modalities, notably multi-omics (single-cell, transcriptomics, proteomics) and histopathology slides.
• Extensive knowledge in modern ML architectures and paradigms like Transformers (ViT), GNNs, foundation models with embedding-based prediction heads (e.g., ABMIL), interpretability methods, and model evaluation & validation principles.
• Proven experience in designing end-to-end ML solutions for complex biological problems, including problem framing, data strategy and model design & evaluation
• Strong fluency in Python and deep learning frameworks (PyTorch, JAX)

Relationship & Strategic Skills

• Stakeholder Management: Proven experience navigating complex, matrixed organizations (Big Pharma experience is a plus). You can present to a VP of R&D in the morning and troubleshoot with a bioinformatician in the afternoon.
• Consulting Mindset: You are not just a support agent; you are a trusted advisor. You have experience in roles such as Field Application Scientist (FAS), Solution Architecture, or Scientific Consulting.
• Feedback Synthesis: Ability to distill complex client complaints or requests into clear, prioritized product requirements.

How to stand out:

• Experience in a startup or innovative environment, showing adaptability and proactiveness.
• A strong existing network within Global Top 20 Pharma R&D.
• Experience specifically with "Foundation Models" or Generative AI in a biological context.
• Track record of high-impact publications (Nature, Cell, NeurIPS).

The candidate journey

To be considered, please submit your CV in English.

We believe in a transparent and collaborative interview process. We need to find a fit for both you and the company. Here is what you can expect after submitting your application:

• Screening: Once you have applied, the hiring team will review your application. If your experience and skills align with the role, you will be invited to a 30-minute introductory call with the Hiring Manager to discuss your background, motivations, and the position in more detail.
• Interviews: Following a successful screening, you will be invited to a series of interviews:
  • Case Study (60 min): You will prepare a mock kick-off document for a client engagement with us to evaluate the model on their desired use-cases, including suggesting interesting use cases for our model and outlining the project plan. We want to see how well you understand the potential use cases for foundation models in the clinical stage of pharma development cycles, and how you would manage a key strategic partner through the deployment and delivery process.
  • Scientific Deep Dive Presentation (30 min): You will briefly present a piece of scientific work to a small panel of our researchers and engineers, led by a senior member of our technical team, and answer Q&S after (10-15 min presentation, 15-20 min Q&A). The content is up to you: it can be your own past research, a relevant paper in the field, or extra points if it’s a specific Bio-AI use case you’ve worked on with a biopharma. The goal is to assess your technical fluency, your ability to facilitate scientific debate, and how you communicate complex concepts to experts.
  • Executive Interview (30 min): A comprehensive discussion with member(s) of our Senior Leadership. This session moves beyond technical competency to focus on long-term vision, values, and mutual potential. This is an opportunity for you to get to know the company better as well.
• Offer: Following the completion of all interviews, our hiring team will make a final decision and will be in touch to share the outcome. Please note that an offer is contingent upon the successful completion of a reference check.
• Onboarding: We are happy to have you joining the team! Once you have accepted and signed your offer, we will be in touch to begin the process of onboarding you.

Why this is a unique opportunity

• A collaborative and mission-driven work environment.
• Competitive salary and equity package.
• Flexible work arrangements, including remote options.
• Opportunities for professional growth and leadership development.
• Shape the future of biology and AI by contributing to groundbreaking work.

Speed is something we fight for every day at Intercom, and we believe Berlin is built for people who share that instinct. We are drawn to Berlin by its rare blend of deep technical talent and rich creative culture – all within a vibrant, globally connected city that’s close to our R&D hubs in Dublin and London. It’s a place where the best of the best technical talent thrive, and where people from around the world are eager to relocate and build ambitious products.

Our ambition is to hire 100 people in Berlin over the year ahead across engineering, AI, data science, product, and design. We believe this is the most exciting time to join, be the founding R&D talent in the region and make a lasting impact as we build the world's number one customer agent!

What's the opportunity? 

Intercom’s Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands.

We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test.

We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy.

What will I be doing? 

• Identify areas where ML can create value for our customers

• Identify the right ML framing of product problems

• Working with teammates and Product and Design stakeholders

• Conduct exploratory data analysis and research

• Deeply understand the problem area

• Research and identify the right algorithms and tools

• Being pragmatic, but innovating right to the cutting-edge when needed

• Perform offline evaluation to gather evidence an algorithm will work

• Work with engineers to bring prototypes to production

• Plan, measure & socialize learnings to inform iteration

• Partner deeply with the rest of team, and others, to build excellent ML products

What skills might I need? 

• Broad applied machine learning knowledge

• 3-5 years applied ML experience

• Practical stats knowledge (experiment design, dealing with confounding etc)

• Intermediate programming skills

• Strong communication skills, both within engineering teams and across disciplines.

• Comfort with ambiguity

• Typically have advanced education in ML or related field (e.g. MSc)

• Scientific thinking skills

Bonus skills & attributes 

• Track record shipping ML products

• PhD or other experience in a research environment

• Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering

• Strong stats or math background

• Visualization, data skills, SQL, matplotlib, etc.

Benefits 

We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us! 

• Competitive salary, annual bonus and equity
• Regular compensation reviews - we reward great work!
• Generous paid time off above statutory minimum
• Generous family leave (maternity, paternity), to let you spend valuable time with your loved ones
• Hybrid working
• MacBooks are our standard, but we also offer Windows for certain roles when needed.
• Unlimited access to Claude Code and best-in-class AI tools; experimentation & building is encouraged & celebrated
• Fun events for Intercomrades, friends, and family!

 
We’re looking for a seasoned Data Scientist to architect the next generation of our campaign optimization systems. You will design and scale the logic that determines which users to target and which incentives to deploy to maximize investment efficiency. If you’re excited to apply Machine Learning and Causal Inference to drive global impact, join us!

 

 
 
With over 200 million users in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people.

We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, national origin, age, or ability.

Our ultimate goal is to make cities for people, not cars. And we need your help on this mission!
 

 
 
You’ll own Bolt’s campaign optimization systems end-to-end, architecting the "brain" that determines how we allocate rider and driver incentives globally. As a Senior Data Scientist, you will be the driving force in elevating our technical standards, pioneering solutions that bridge the gap between academic research and product development. You will serve as a technical "North Star"—mentoring colleagues and setting the bar for rigorous, maintainable data products that directly shape the experience of over 200 million customers worldwide.
 

 
 
  

• Lead the technical vision for our campaign optimization roadmap, translating high-level objectives into data science products.
• Architect and deploy end-to-end uplift models and optimization systems that maximize our investment efficiency.
• Design and execute advanced experimentation frameworks to reliably measure campaign incrementality.
• Set the gold standard for technical excellence by championing rigorous statistical and engineering practices.
• Serve as a mentor and advisor on highly technical challenges.
• Partner with Product, Engineering, and Operations to identify opportunities and develop pragmatic solutions that solve intricate business problems.

 
 

• Pragmatic problem solver, able to work autonomously from research to production deployment.
• 5+ years of experience in applied ML; experience in a growth role (marketplace pricing or incentives) is a plus.
• Exceptional knowledge of ML, statistics with hands-on experience in causal inference/ML.
• Expert proficiency in Python and SQL.
• A natural mentor who enjoys leveling up those around you and can explain the "why" behind complex mathematical concepts.
   

 
Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying!
 

 
 

• Play a direct role in shaping the future of mobility.
• Impact millions of customers and partners in 600+ cities across 50+ countries.
• Work in fast-moving autonomous teams with some of the smartest people in the world.
• Accelerate your professional growth with unique career opportunities.
• Get a rewarding salary and stock option package that lets you focus on doing your best work.
• Enjoy the flexibility of working in a hybrid mode with a minimum of 3 days in the office each week to foster strong connections and teamwork.
• Take care of your physical and mental health with our wellness perks.
   

  *Some perks may differ depending on your location and role.

 
We’re looking for a seasoned Data Scientist to architect the next generation of our campaign optimization systems. You will design and scale the logic that determines which users to target and which incentives to deploy to maximize investment efficiency. If you’re excited to apply Machine Learning and Causal Inference to drive global impact, join us!

 

 
 
With over 200 million users in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people.

We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, national origin, age, or ability.

Our ultimate goal is to make cities for people, not cars. And we need your help on this mission!
 

 
 
You’ll own Bolt’s campaign optimization systems end-to-end, architecting the "brain" that determines how we allocate rider and driver incentives globally. As a Senior Data Scientist, you will be the driving force in elevating our technical standards, pioneering solutions that bridge the gap between academic research and product development. You will serve as a technical "North Star"—mentoring colleagues and setting the bar for rigorous, maintainable data products that directly shape the experience of over 200 million customers worldwide.
 

 
 
    

• Lead the technical vision for our campaign optimization roadmap, translating high-level objectives into data science products.
• Architect and deploy end-to-end uplift models and optimization systems that maximize our investment efficiency.
• Design and execute advanced experimentation frameworks to reliably measure campaign incrementality.
• Set the gold standard for technical excellence by championing rigorous statistical and engineering practices.
• Serve as a mentor and advisor on highly technical challenges.
• Partner with Product, Engineering, and Operations to identify opportunities and develop pragmatic solutions that solve intricate business problems.

 
 

• Pragmatic problem solver, able to work autonomously from research to production deployment.
• 5+ years of experience in applied ML; experience in a growth role (marketplace pricing or incentives) is a plus.
• Exceptional knowledge of ML, statistics with hands-on experience in causal inference/ML.
• Expert proficiency in Python and SQL.
• A natural mentor who enjoys leveling up those around you and can explain the "why" behind complex mathematical concepts.
   

 
Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying!
 

 
 

• Play a direct role in shaping the future of mobility.
• Impact millions of customers and partners in 600+ cities across 50+ countries.
• Work in fast-moving autonomous teams with some of the smartest people in the world.
• Accelerate your professional growth with unique career opportunities.
• Get a rewarding salary and stock option package that lets you focus on doing your best work.
• Enjoy the flexibility of working in a hybrid mode with a minimum of 3 days in the office each week to foster strong connections and teamwork.
• Take care of your physical and mental health with our wellness perks.
   

  *Some perks may differ depending on your location and role.

Position: Field Applications Scientist I, EMEA

Position Type: Full-Time

Department: Scientific Support

Location: DACH region (Germany / Austria / Switzerland). Remote. Must be close to a major airport (within 50 kms).

Experience: MS required; 4+ years experience in a Field Applications role 

Position Summary

Watchmaker Genomics (WMG) is inviting applications for the full-time position of Field Applications Scientist I, EMEA (remote) based in the DACH region.

This position reports to the Associate Director, Field and Automation Support and will be mainly responsible for providing field technical support for Watchmaker’s Next-Gen Sequencing (NGS) and precision enzyme product portfolios. This position will support the EMEA technical team by providing pre- and post-sales technical and scientific support, including presenting technical content to customers and distributors, co-travel with sales team members, attending and/or presenting at conferences and assisting with various marketing activities. This position is field based, with up to 75% travel within EMEA (potential for international travel outside EMEA). 

Prior experience with providing field application support is required. The successful candidate will be self-motivated, proactive, and thrive in a dynamic, fast-paced working environment contributing directly to our company culture and success.

The position is expected to have a deep technical understanding of our current product portfolio, maintain knowledge of current and new NGS products, workflows-associated applications, competitor products and NGS automation support offerings, and identify and escalate changes in the market dynamics. This position is also accountable for providing customer feedback on WMG products, in addition to identifying unmet customer needs that will enable the development of new and innovative products.

Responsibilities

• Responsible for providing pre- and post-sales technical and scientific support, both onsite and remote, for customers and distributors across WMG’s NGS and precision enzyme product portfolio. 
• EMEA-based travel (up to 75%) activities including co-travel with sales team members, meetings with key customers, providing training and troubleshooting, and participating in trade shows/conferences. Possible opportunity for further international travel.
• Provides deep product knowledge to solve customer challenges. Triages issues, troubleshoots investigations, and identifies solutions.
• Creation of training material, and presenting technical content to new or current customers or distributors.
• Inform and implement processes as a part of our EMEA-field based scientific support organization.
• Maintain expert-level knowledge of current and new NGS products and workflows, our precision enzyme portfolio and associated applications, competitor products and NGS automation support offerings. 
• Provide customer and market feedback on WMG products; Identify and communicate unmet customer needs that will aid in the development of new and innovative products.
• Work closely with the commercial team to identify and support collaborations with leading research institutions and industry partners to accelerate the sales cycle, including both pre-sales and post-sales troubleshooting. 
• Support marketing activities including generation of customer-facing technical content (i.e. posters, app/tech notes, white papers, webinars) as well as participating in and presenting at trade shows/conferences.
• Participate in sales, marketing, and product strategy meetings when appropriate. 
• Follow best practices and documentation requirements for customer-related activities and events in CRM.
• Additional duties as required within the remit and responsibilities of the role.

Required Qualifications and Experience

Relevant experience providing field-based applications support for next-generation sequencing (NGS) experiments and/or other advanced genomics applications. Relevant experience includes working in high-throughput sequencing labs developing, optimizing and troubleshooting NGS workflows both manually and on automated platforms and managing large sequencing projects. 

Qualified candidates will have a proactive approach with a can-do attitude, and be great communicators with a high level of self-motivation. Candidates will also have a strong desire to continually improve, learn and collaborate to help WMG stay at the forefront of exciting new applications spaces. Candidates will be able to demonstrate a high standard experience to our customer base, excel in the art of troubleshooting, and take ownership and pride in their work.

Candidates will have the courage to initiate discussions with customers to challenge the current "status quo" and have the confidence to drive change and adoption of new concepts. Full product training will be provided.

The following skills and experience are requirements for the position:

• MSc in Genetics, Molecular Biology, Biochemistry or related field
• 4+ Years experience within NGS field applications 
• Advanced knowledge of and practical experience with experimental design, applications/assay development, NGS library preparation, PCR, qPCR, good lab practices, and troubleshooting. Automation knowledge of NGS assays is a plus. 
• Ability to travel up to 75% of time 
• Strong customer consultative skills which includes application of scientific knowledge and analysis, exceptional customer engagement, and fostering of customer relationships
• High self-motivation and must have demonstrated ability to work in a collaborative team environment
• Experience with CRM software (particularly Salesforce.com) highly desirable
• Excellent verbal and written communication skills
• Fluent in English (required), multiple languages is a plus (German, preferred)

Application Requirements 

To apply for the position, please submit the following in a PDF format on watchmakergenomics.com: 

• Letter of motivation (upload where it says cover letter)
• Resume or Curriculum vitae, highlighting relevant qualifications and experience

Applications without a Letter of Motivation will not be considered.

Applications will be accepted on a rolling basis and the position will remain open until filled; however, early submission is encouraged as review will begin immediately.

If selected to participate in the interview process, the names and contact information of three professional references who are able to assess your suitability for the position in terms of the specified requirements will be requested.

*** NO RECRUITMENT AGENCIES PLEASE

We are only accepting direct applications for this position. We are not working with external recruiters or agencies at this time. Unsolicited resumes or candidate submissions from third-party recruiters will not be considered and will be deemed the property of Watchmaker Genomics.

*** WE ARE AN EQUAL OPPORTUNITY/AFFIRMATIVE ACTION EMPLOYER

Watchmaker Genomics is committed to being an equal opportunity employer and creating a culturally diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, or veteran status or any other characteristics as protected by applicable law..

This position may be subject to pre-employment checks, including driving history check, drug screening and a background check for any convictions directly related to its duties and responsibilities. All pre-employment checks will comply with all applicable federal, state, and local laws.

Role

As a Senior Research Scientist focused on Robotic Foundation Models, you will be responsible for the design and implementation of systems that enable the training, deployment, and utilization of large-scale AI models for robotics. You will guide technical direction, mentor engineers, and ensure the development of robust, scalable ML models  required to make robots significantly more capable in real-world environments. Your work will empower both internal teams and external partners by providing accessible tools and infrastructure for injecting advanced machine learning techniques into robotic applications.

How your work moves the mission forward

• Lead the design and implementation of infrastructure and architecture of large-scale robotic foundation models.
• Oversee the training and deployment of robust ML models for high-performance robotic applications.
• Empower ML researchers and engineers with accessible tools and infrastructure for developing and applying AI techniques in robotics.
• Collaborate with product and engineering teams to define infrastructure requirements and deliver successful solutions for partners and customers.

Skills you will need to be successful

• PhD in Computer Science / Engineering with a specialization in Machine Learning and / or Robotics.
• Experience collaborating on medium to large software projects for at least 4 years.
• Experience in programming Python / C++ and machine learning frameworks (Tensorflow, JAX).
• Demonstrable experience with offline Reinforcement / Imitation Learning in a robotics context.
• Proven ability to work with a team, setting directions and driving towards solutions.

Skills that will differentiate your candidacy

• Academic track record of publications in the field of offline Reinforcement / Imitation Learning in Robotics.
• Experience with Robotic Foundation Models / Vision-Language-Action Models.
• Experience with Online Reinforcement Learning and / or Computer Vision for Robotics.
• Experience with deploying ML services at scale, e.g., via cloud computing and containerization (Google Cloud, Docker, Kubernetes), databases (SQL, no-SQL), and service-oriented architecture frameworks.