We are looking for passionate technologists to join our Pre-Sales organization to ensure that our growth is grounded and guided by strong technical alignment with our platform and the needs of our customers.

MongoDB Pre-Sales Solution Architects are responsible for guiding our customers and users to design and build reliable, scalable systems using our data platform. Our team is made up of seasoned technical sales professionals, software architects, entrepreneurs, and developers who take direct responsibility for customer success, including the design of their software, deployment, and operations. You'll work closely with our sales executives, helping customers solve business problems by leveraging our solutions, playing a key role in winning deals and driving the business forward. You'll be a trusted advisor to a wide range of users from startups to the world's largest enterprise IT organizations. 

We are looking to speak to candidates who are based in Tel Aviv for our hybrid working model.

As an ideal candidate, you will have:

• 5 to 8  years of related industry experience, ideally 2 years of experience in a customer facing role
• Minimum of 2 years experience with modern scripting languages (e.g. Python, Node.js, SQL) and/or popular programming languages (e.g. C/C++, Java, C#) in a professional capacity
• Experience implementing scalable and highly available distributed systems in the cloud and on-prem
• Demonstrated ability to work with customers to review complex architecture of existing applications, providing guidance on how to improve by leveraging technology
• Excellent presentation, communication, and interpersonal skills, with the ability to convey complex technical and business concepts in a clear and compelling manner to technology and business leadership
• Ability to work with a cross functional sales team to formulate and execute an end to end deal cycle
• The ability to travel up to 25%
• A Bachelor’s degree or equivalent work experience

You may also have:

• Experience developing, deploying, or supporting applications with any of the major cloud providers 
• Experience working in a technical pre-sales capacity 
• Experience with database programming and data models 
• Experience in data engineering or AI/ML projects
• Understanding of popular sales methodologies/ frameworks such as MEDDPICC/ Command of the Message
• A MongoDB Certification
• A Cloud Provider Certification

What you do at MongoDB:

In this role, you will work on complex opportunities where analysis of situations or data requires an in-depth evaluation of various factors. You will:

• Design and Architect: Design scalable and performant applications, systems and infrastructure for large software projects leveraging MongoDB
• Customer Advising and Value Articulation: Guide customers on architecture patterns and optimisation strategies for MongoDB, while clearly communicating its business value to the relevant stakeholders
• Sales Partnership: Collaborate with the sales team to drive account success through account planning, opportunity prioritization/qualification and pipeline generation strategy, while taking ownership of the technical aspects (including but not limited to technical discovery, demos, proof of value, presentations, sizing and documentation)
• Demand Generation: Proactively generate demand within the sales territory through self-driven technical initiatives, participation in events such as industry trade shows and account-based marketing events
• Customer Success: Foster strong customer relationships, build champions and ensure customer success and satisfaction
• Innovation and Improvement: Continuously seek opportunities to innovate and improve MongoDB solutions and processes (e.g. by relaying field feedback to the product team), as well as proactively mentor other Solutions Consulting team members 
• Personal Training and Development: Engage in ongoing training and professional development to stay abreast of MongoDB product suite as well as industry trends

What you will learn:

MongoDB Product Suite Mastery:

• Core Database Server: Master the fundamentals and advanced features of MongoDB's core database
• Atlas and Advanced Services: Gain expertise in Atlas (fully managed cloud database service), Atlas Stream Processing, Atlas Data Lake, Atlas Full-Text Search, Atlas Vector Search, and Charts
• Relational Migrator: Learn to migrate from relational databases seamlessly

Market-Relevant Technologies:

• Hyperscaler Ecosystem: Gain expertise in designing complex systems utilizing cloud services on hyperscaler platforms 
• Complementary Technologies: Enhance your skills with partner and complementary technologies such as Apache Kafka and Kubernetes

Modern Architecture Design:

• Design Patterns and Methodologies: Embrace best practices in microservices, DevOps, cloud, and security
• Cutting Edge RAG and AI Architectures: Help customers on their generative AI journey and working with industry leading partners in the space

Sales Techniques and Soft Skills:

• Effective Communication: Master presentations, demonstrations, and whiteboarding
• Client Interaction: Develop strategies for discovery and objection handling

Industry Insights:

• Diverse Market Verticals: Gain exposure to a broad spectrum of interesting use cases across various industries

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform, the most widely available, globally distributed database on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and over 60,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB is an equal opportunities employer.

Req ID: 426128

The role

Nebius is looking for a Senior Data Scientist to build and deploy time series forecasting and classical machine learning models that support core business planning and operational decisions. You will own problems end-to-end, from data exploration and feature engineering to model deployment and monitoring, working with large-scale, real-world datasets.

The role emphasizes strong statistical thinking, robust modeling, and production reliability over experimentation with trendy frameworks. Your work will directly impact forecasting accuracy, resource planning, and key business metrics.

You’re welcome to work in our offices in Tel Aviv.

Your responsibilities will include: 

• Time series forecasting. Design, build, and maintain forecasting models (e.g., demand, usage, capacity). Evaluate performance using appropriate metrics and improve accuracy over time.
• Classical ML modeling. Develop and deploy models using regression,Binary classifcatiom ,  tree-based methods, and other well-established approaches where they provide the best trade-off between performance, interpretability, and maintainability.
• Feature engineering & data preparation. Build robust pipelines for data cleaning, transformation, and feature generation (including time-based features, seasonality, and external signals).
• Model evaluation & monitoring.Define evaluation frameworks, backtesting strategies, and monitoring to ensure models remain stable and reliable in production.
• Production & MLOps. Deploy models into production environments, collaborate on pipeline orchestration, and ensure reproducibility and version control.
• Exploratory analysis. Analyze large datasets to identify patterns, anomalies, and drivers of change in time-dependent behavior.
• Stakeholder collaboration. Work closely with business and product teams to define forecasting needs, align on success metrics, and translate model outputs into actionable insights.
• Cross-domain contribution. Contribute to adjacent data science areas (e.g., LLM-based systems) as needed, ensuring shared ownership and continuity across team responsibilities.

We expect you to have: 

• Experience as a data scientist working in production environments (5+ years).
• Experience with time series modeling and forecasting techniques.
• Experience building reliable data pipelines and working with large datasets.
• Experience with modern data science tools and ecosystems using Python (e.g., NumPy, Pandas, Scikit-learn, deep learning frameworks).
• Strong SQL skills and experience working with large datasets.
• Strong foundation in statistics and machine learning fundamentals.
• Background in Computer Science, Statistics, Mathematics, Industrial Engineering, Economics, or a related field (Master’s degree or equivalent).
• Demonstrated ability to take models from idea to production and ensure ongoing value.
• Demonstrated ability to apply structured thinking and robust evaluation in forecasting problems.
• Strong communication skills and ability to explain model outputs, uncertainty, and limitations.
• Working knowledge of spoken and written English.

It will be an added bonus if you have: 

• Experience working in cloud environments (preferably Azure).
• Experience with MLOps tools and production model lifecycle management.
• Experience with workflow orchestration tools such as Apache Airflow.
• Familiarity with LLM-based systems (e.g., evaluation, RAG pipelines) in applied settings.

Similarweb is the leading digital intelligence platform used by over 3500 global customers. Our wide range of solutions power the digital strategies of companies like Google, eBay, and Adidas.

We help our customers succeed in today's digital world by giving them access to data-driven insights, competitive benchmarks, strategic analysis, and more.

In 2021, we went public on the New York Stock Exchange, and we haven't stopped growing since!

We are looking for a Product Manager to join our Gen AI Intelligence team, owning the end-to-end data platform that powers our next-generation products.

The Opportunity: Why This Role, Why Now

The marketing world is undergoing its biggest shift in a decade. Discovery is no longer just "search"—it's increasingly mediated by AI. Users are asking questions in ChatGPT, Perplexity, and Google AI Overviews, and the traditional "search → click → website" funnel is fragmenting. This shift has created a new discipline: Generative Engine Optimization (GEO) and AI Engine Optimization (AEO).

Similarweb is uniquely positioned to lead this space. We have proprietary data that reveals not just what AI shows users, but what users actually do next—which channels they visit, where demand flows, and how brands win (or leak) visibility. Our mission is to help marketers understand their visibility in AI platforms, connect that visibility to downstream business outcomes, and take action to improve.

The Impact of This Role

As a Product Manager for our GenAI team*, you will own the data backbone of Gen AI Intelligence. You'll need to be sharp on how to combine, utilize, and analyze diverse data sources** to answer the questions our customers need answered.

You'll work at the intersection of our Data Science team, Data Engineering team, and Platform team—turning raw data assets into user-facing products. But building the right products requires understanding the domain: you'll dig into SEO/GEO workflows, spend time with customers and design partners, and learn how marketing teams actually operate. The goal is to let user context drive your data decisions.

Your core mandate:

• Own a product area end-to-end within Gen AI Intelligence—from the underlying data and pipelines, through the user-facing experiences, to how customers extract value via APIs and integrations.
• Define what data we need, how we structure it, and how we expose it to users and downstream systems
• Deeply understand user workflows and jobs-to-be-done to identify the highest-leverage data solutions
• Partner with Data Science to translate models and extractions into usable, reliable data pipelines
• Ensure data quality, coverage, and governance across our Gen AI data estate
• Drive product development end-to-end: from discovery through definition, prototyping, design, development, and deployment—with continuous iteration
• Collaborate across a multi-disciplinary team: data scientists, data engineers, full-stack developers, UX designers, product marketers, and business stakeholders

What you'll do day-to-day

• Obsess over user context: Understand how SEO practitioners, content marketers, and marketing leaders actually work—what questions they're trying to answer, what data would unlock value, and where current solutions fall short
• Define data products end-to-end: From discovery through definition, schema design, pipeline development, and delivery—ensuring consistent quality and velocity
• Connect data to user outcomes: Work closely with product teams that consume your data (reporting UX, recommendations, APIs) to ensure the data products actually solve user problems
• Partner deeply with Data Science and Engineering: Translate DS models into production-ready data products; define requirements for data engineering pipelines; prioritize platform investments; 
• Define the core metrics, datasets, reports, and insights that will be made available to our users through our SaaS platform, APIs and MCPs.
• Own data quality and coverage: Define metrics for data completeness, accuracy, and freshness; build feedback loops to continuously improve
• Make tradeoffs with evidence: Use quantitative and qualitative analysis and user research to prioritize ruthlessly—not everything can be built, so you need to know what matters most

This is the perfect job for someone who has:

Must-haves:

• 3+ years as a Product Manager on data-centric products (data platforms, analytics products, ML-powered features, or similar)—you've shipped data products that users depend on
• Experience working in a data company or on data products where the core value proposition was derived from data (not just "we use data")
• Strong analytical and data skills: You're comfortable querying data, analyzing patterns, and making data-informed decisions. You can hold your own in conversations about data modeling, schemas, and pipelines
• Deep user empathy and research skills: You don't just build what stakeholders ask for—you dig into user workflows and jobs-to-be-done to find the real problem worth solving
• Experience working with Data Science and Data Engineering teams: You know how to translate between DS/ML outputs and production systems, and you understand the tradeoffs involved
• Strong communication skills: You can write a clear PRD, present to leadership, and align cross-functional teams around a shared vision

Strong pluses:

• SQL proficiency: You can write queries to explore data, validate hypotheses, and QA outputs
• Python or other scripting ability: You can prototype analyses, automate checks, or dig into data yourself when needed
• Experience in digital marketing, SEO, or adjacent domains: Understanding of how marketers think about search, content, and visibility
• Experience with B2B SaaS and enterprise customers: You understand long sales cycles, packaging, and the needs of mid-market/enterprise buyers

Mindset:

• Curiosity over credentials: You want to understand how things work, not just ship features
• Bias for action: You'd rather test a hypothesis with an imperfect solution than wait for perfect information
• Comfort with ambiguity: GEO/AEO is a new space—you'll help define what "good" looks like, not just execute a playbook

Why you'll love being a Similarwebber

You'll work on a genuinely new problem space: GEO and AI visibility is an emerging category. You won't be iterating on a mature product—you'll be defining what the product should even be.

You'll have access to unique data assets: Similarweb's real-user behavioral data is genuinely differentiated. You'll get to figure out how to turn that into user value—a rare opportunity.

You'll actually love the product you work with: When we asked our employees why they chose to come work at Similarweb, 99% of them said "the product." Imagine how exciting your job is when you get to work with the most powerful digital intelligence platform in the world.

You'll find a home for your big ideas: We encourage an open dialogue and empower employees to bring their ideas to the table. You'll find the resources you need to take initiative and create meaningful change within the organization.

We offer competitive perks & benefits: We take your well-being seriously, and offer competitive compensation packages to all employees. We also put a strong emphasis on community, with regular team outings and happy hours.

You can grow your career in any direction you choose: Whether it's Career Week, personalized coaching, or our ongoing learning solutions, you'll find all the tools and opportunities you need to develop your career right here.

Diversity isn't just a buzzword: We strive to create a workplace that is reflective of the communities we serve, where everyone is empowered to bring their full, authentic selves to work. We are committed to inclusivity across race, gender, ethnicity, culture, sexual orientation, age, religion, spirituality, identity and experience.

We will handle your application and information related to your application in accordance with the Applicant Privacy Policy available here.

At Similarweb, we are revolutionizing the way businesses interact with the digital world by revealing to them everything that happens online. 

Our unique data and solutions empower thousands of customers globally, including industry giants like Google, eBay, and Adidas, to make game-changing decisions that drive their digital strategies.

In 2021, we went public on the New York Stock Exchange, and we continue to reach new heights! Come work alongside Similarwebbers across the globe who are bright, curious, practical, and good people.

About the Role

We’re looking for a Senior Marketing Operations Manager to take ownership of our marketing infrastructure, automation, technology stack, processes, and data strategy.

At Similarweb, Marketing Operations plays a critical role in connecting data, systems, and teams to drive scalable growth across both Sales-Led (SLG) and Product-Led (PLG) motions. This role sits at a key intersection within our Marketing organization, enabling alignment across teams, technologies, and processes.

You will be both a hands-on builder and a strategic partner, working closely with Lifecycle Growth, Product Marketing, Demand Generation, BI, MIS and GTM teams to design and scale high-impact marketing workflows.

You’ll play a central role in transforming how we operate, bringing a modern, AI-first approach to marketing operations, simplifying complex legacy processes, and driving measurable business impact.

Key Responsibilities

• Own and optimize marketing automation platforms, building scalable multi-channel campaigns, lifecycle journeys, and nurture programs
• Lead advanced audience segmentation and ensure seamless lead flow across SLG and PLG funnels
• Design and implement scalable marketing processes, including campaign execution, lead management, and data governance
• Set up and maintain lead capture integrations while operating data enrichment strategies using internal and external sources, ensuring accurate data flow and improving segmentation, targeting, and personalization
• Own data governance across marketing systems and CRM, ensuring high standards of accuracy, consistency, and scalable data structures across multiple objects
• Collaborate cross-functionally to translate business needs into operational solutions and drive alignment on GTM and KPIs
• Analyze campaign and funnel performance, delivering actionable insights and defining measurement frameworks with BI and Analytics teams
• Drive AI innovation, including redesigning workflows and implementing AI-driven solutions

What We’re Looking For

Experience & Background

• 3–5+ years of experience in Marketing Operations, Lifecycle, or Growth Operations within B2B SaaS
• Hands-on experience with CRM systems (e.g., Salesforce) and marketing automation platforms (e.g., Marketing Cloud, HubSpot), including managing large-scale datasets
• Strong expertise in lifecycle marketing, segmentation, and building end-to-end marketing processes with an omnichannel approach
• Experience implementing and maintaining marketing models (e.g., SQL, Intent, MQL scoring)
• Proven experience leveraging AI in marketing or operations, including building and implementing AI-driven solutions
• Ability to operate both strategically and hands-on in a fast-paced environment
• Experience streamlining large-scale data flows across marketing systems and CRM
• Strong project management and communication skills, with the ability to manage multiple stakeholders and priorities
• Experience leading marketing platform implementations and managing them at an admin level, including overseeing martech stacks, budgets, and vendors

Why you’ll love being a Similarwebber:

You’ll actually love the product you work with: Our customers aren’t our only raving fans. When we asked our employees why they chose to come work at Similarweb, 99% of them said “the product.” Imagine how exciting your job is when you get to work with the most powerful digital intelligence platform in the world.

You’ll find a home for your big ideas:  We encourage an open dialogue and empower employees to bring their ideas to the table. You’ll find the resources you need to take initiative and create meaningful change within the organization. 

We offer competitive perks & benefits: We take your well-being seriously, and offer competitive compensation packages to all employees. We also put a strong emphasis on community, with regular team outings and happy hours.

You can grow your career in any direction you choose: Interested in becoming a VP or want to transition into a different department? Whether it’s Career Week, personalized coaching, or our ongoing learning solutions, you’ll find all the tools and opportunities you need to develop your career right here.

Diversity isn’t just a buzzword: People want to work in a place where they can be themselves. We strive to create a workplace that is reflective of the communities we serve, where everyone is empowered to bring their full, authentic selves to work. We are committed to inclusivity across race, gender, ethnicity, culture, sexual orientation, age, religion, spirituality, identity, and experience. Our culture of equality and mutual respect also helps us better understand and serve our customers in a world that is becoming more global, more diverse, and more digital every day.

Hi. I’m Ron, Eon’s co-founder and CTO.

I’ll be direct: Eon is at the most crucial moment in its journey, and we are looking for highly skilled engineers to help bring this company to the next stage. We’ve done what no one else has managed to do - make backups actually useful, building a cloud-native backup and recovery platform for enterprises running across multi-cloud environments. Eon turns backup data into a strategic asset, with visibility, control, and usability across the board. We’re trusted by global enterprises, and we’re building a once-in-a-generation company.
In other words: NOW  is the time to join us.

About the Role 

We’re looking for a Senior Backend Developer who is ready to build at the highest level. You'll design and scale backend systems that power the core of our platform. You'll work directly with me to deliver features that enterprises can't live without. You'll work with top talent like yourself - with opportunities for peer learning and the chance to mentor others. We're looking for people who approach challenges as opportunities to develop solutions. Here, you'll have the opportunity to drive innovation from within and shape the way in which we develop.

This is not a role where you're buried in bureaucracy. You'll see your work ship quickly, shape the company itself, and directly impact how Fortune 500 companies handle their most critical cloud infrastructure.

What You’ll Do

• Build backend services that can scale across multi-cloud environments.
• Work directly with other engineers and product leads to deliver end-to-end solutions that matter.
• Push performance to the limit - speed, reliability, and security at enterprise scale.
• Write code you’re proud of: clean, testable, maintainable.
• Make key architecture and design decisions.
• Bring your perspective straight to me and - I want your voice.
• Operate with autonomy and own your own work. (I mean it.)

Who You Are

Must-Haves

• You are the best in your team. 
• You want to work with the very best.
• You thrive when you’re trusted with real ownership and responsibility.
• You move quickly, collaborate well, and know how to make an impact.
• You’re hyper-motivated to build something epic.

Nice-to-Haves

• Familiarity with AWS, Azure, GCP, or all of the above.
• Comfort working in high-scale, data-heavy environments where performance matters.

Why Join Us?

Eon is the fastest growing startup in cloud infrastructure and cyber security. We are extremely well-funded, trusted by the biggest players in the industry. But we’re also lean, agile, and flat. You’ll work directly with me and be part of the founding team, shape product direction, and see your work change the trajectory of enterprises around the world. We demand a lot because what we’re building is big. 

We take care of our people, and we make sure your journey here will be enjoyable and worth the ride. 

If you’re ready to be part of an incredible team and do the best work of your career, now’s  the time to apply, even if your experience doesn’t tick every box.

DevOps Engineer

Hi. I’m Ron, Eon’s co-founder and CTO.

I’ll be direct: Eon is at the most crucial moment in its journey, and we’re looking for exceptional engineers to help take the company to the next level.

We’ve done what no one else has managed to do — make backups actually useful. We built a cloud-native backup and recovery platform for enterprises running across multi-cloud environments. Eon turns backup data into a strategic asset, giving enterprises visibility, control, and real usability at scale. We’re trusted by global enterprises, and we’re building a once-in-a-generation company.

In other words: NOW is the time to join us.

About the Role

We’re looking for a DevOps Engineer who is ready to operate at the highest level.

This is a core role at Eon. You’ll own the infrastructure that powers our platform across AWS, Azure, and GCP, enabling massive scale, performance, reliability, and security. You’ll work directly with me and the engineering leadership to design and evolve our cloud architecture, CI/CD pipelines, and Kubernetes environments.

This is not a role for someone who wants tickets and hand-holding. You’ll have real ownership, real impact, and the autonomy to shape how we build and operate our platform.

What You’ll Do

• Design, build, and operate multi-cloud infrastructure at enterprise scale.

• Build and evolve CI/CD pipelines that enable fast, safe, and reliable deployments.

   

• Own infrastructure as code using Terraform (and CloudFormation/Bicep where relevant).

• Operate and troubleshoot managed Kubernetes environments (EKS, AKS, GKE).

• Push infrastructure performance, reliability, and availability to the limit.

• Implement cloud security best practices (IAM, secrets, encryption, network security).

• Partner closely with backend, security, and data teams to enable high-velocity development.

• Make key architectural decisions and influence the future of Eon’s platform.

• Bring your opinions, ideas, and instincts to the table — I want to hear them.

Who You Are

Must-Haves

• You are one of the strongest engineers on your team.

• You thrive when given ownership, responsibility, and trust.

• You move fast, think clearly, and execute with precision.

• You’re motivated by hard problems and real impact.

• You want to work with people who raise your bar every day.

Technical Requirements

• 4+ years of experience in DevOps / Cloud Engineering / SRE.

• Solid experience with Kubernetes and managed services (EKS / AKS / GKE).

• Strong hands-on experience with at least one major cloud provider (AWS, Azure, or GCP).

• Proven experience with Terraform in production environments.

• Experience building and maintaining CI/CD pipelines at scale.

Nice-to-Haves

• Multi-cloud experience (AWS + Azure + GCP).

• Experience in high-scale, data-heavy systems.

• Strong security mindset (DevSecOps, least privilege, defense in depth).

• Experience supporting fast-growing SaaS platforms.

Why Join Eon?

Eon is one of the fastest-growing startups in cloud infrastructure and cyber security. We’re extremely well-funded, trusted by global enterprises, and tackling problems that actually matter.

At the same time, we’re lean, flat, and execution-focused. You’ll work directly with me, be part of the core team shaping the company, and see your work change how enterprises protect and operate their cloud infrastructure.

We demand a lot — because what we’re building is big.
And we take care of our people — because great companies are built by great teams.

If you’re ready to do the best work of your career and build something truly meaningful, now is the time to apply — even if you don’t tick every single box.

Why this role matters
AI makes code generation easier, but proving that code works in production is still hard. This role focuses on closing that gap by building runtime technology that enables safe, real-time validation inside live applications, so engineers and AI agents can verify fixes, changes, and assumptions where they actually matter.

Responsibilities

• Build low-overhead runtime instrumentation and data capture in customer processes across Java, C++ and related environments
• Ensure compatibility across runtime versions, frameworks, and deployment environments such as containers, Kubernetes, Windows, and Linux
• Build backend services to securely define, distribute, and manage agent actions at scale
• Own agent-backend APIs and protocols, including versioning, compatibility, and release strategy across a large installed fleet
• Drive profiling and benchmarking to minimize runtime overhead and enforce 
• performance budgets

Requirements

Must have

• Strong C++ skills with production experience, especially in performance and memory safety
• Production experience with Java and/or .NET, particularly in core libraries, frameworks, or runtime-adjacent components
• Experience building high-performance systems under latency, CPU, and memory constraints
• Strong backend engineering experience designing and operating production services and APIs

Nice to have

• Hands-on experience with profilers and runtime instrumentation technologies, such as:
• Java: JVMTI, bytecode instrumentation, ASM, Byte Buddy, JIT/GC awareness, safe attachment patterns
• .NET: CLR Profiling APIs, ICorProfiler, IL rewriting, managed/unmanaged interop

We are looking for a highly skilled Senior Machine Learning Engineer to lead our transition from on-demand, third-party LLM APIs to a fully self-hosted, scalable model ecosystem.

Our core product is an advanced, agentic support chatbot capable of complex reasoning, API tool calling, database lookups, and orchestrating specialized Small Language Models (SLMs) for targeted NLP tasks. As we scale, our current deployment infrastructure (AWS SageMaker) is becoming unsustainable. You will be responsible for architecting, deploying, and optimizing an infrastructure capable of supporting 50 to 100 distinct models ranging from 100M to 70B parameters.

What You’ll Do:

• Inference Optimization: Deploy and manage large-scale models using high-performance inference engines (like vLLM) to ensure low latency and high throughput for our agentic chatbot.
• Agentic Workflows: Develop and refine the chatbot's agentic capabilities, ensuring reliable tool-use, routing, and interactions between massive LLMs and specialized SLMs.
• Model Fine-Tuning: Design and execute fine-tuning strategies to improve model accuracy on specific domain tasks and tool-calling execution.
• Rigorous Evaluation: Build comprehensive offline and online evaluation frameworks to constantly measure model performance and business impact through structured A/B testing.

What We’re Looking For:

Core Engineering & AI Frameworks

• Strong proficiency in Python and Bash scripting.
• Deep experience with PyTorch and the Hugging Face ecosystem.
• Experience using AI coding assistants natively in the terminal, specifically Claude Code, to accelerate development workflows.

LLMs, Inference & Agents

• Proven experience deploying models using vLLM, TGI, or similar high-performance inference servers.
• Strong fundamental understanding of LLM architectures, attention mechanisms, and generation parameters.
• Hands-on experience building Agentic systems (ReAct, function/tool calling, RAG).
• Expertise in fine-tuning strategies (e.g., SFT, RLHF, DPO) and parameter-efficient techniques (PEFT/LoRA).

Statistics & Model Evaluation

• Offline Metrics: Deep understanding of classification/summarization metrics (Precision, Recall, F1, AUC) and retrieval metrics (MRR, NDCG, Precision/Recall @ k).
• Online Metrics & A/B Testing: Strong statistical foundation to design and analyze A/B tests safely, including the use of t-tests, Mann-Whitney U tests, and bootstrapping techniques.

Bonus Points

• Containerization & Orchestration: Experience with Ray for orchestrating large-scale model deployments across multi-GPU clusters.
• Model Quantization: Experience with memory optimization techniques like AWQ, GPTQ, GGUF, or FlashAttention to fit 70B models efficiently onto hardware.
• API Development: Proficiency in building robust, asynchronous microservices using FastAPI to serve model requests.

• Knowledge of Data Engineering principles: dataset collection, cleaning, processing, and scalable storage.

Experience with core MLOps practices, including dataset versioning (e.g., DVC), experiment tracking (e.g., Weights & Biases, MLflow), and model registries.