Jobs ML / AI Engineer

Job Description

1+ years Mainframe development experience

Experience in the following technical areas:

• COBOL
• DB2
• CICS

Nice to have experience:

• DFSORT and SYNCSORT
• Endevor
• PL/SQL
• VisualStudio Code
• Postgres

Experience with CI/CD tools such as Azure DevOps
Hands-on experience with the entire software development lifecycle (SDLC)
Excellent analytical, problem-solving.
Ability to work effectively in a fast-paced and dynamic environment.
Strong comunication skills

Job Responsibilities

• Work as part of a team in a mainframe environment;
• Design, develop, and debug complex COBOL programs
• Design and maintain real-time transaction processing programs to ensure sub-second response times for end-users using CICS.
• Use DFSORT and SYNCSORT to optimize data manipulation, ensuring that massive datasets are processed with minimal CPU overhead.
• Manage and manipulate relational data via DB2, including complex SQL tuning and the development of PL/SQL stored procedures.
• Perform peer reviews of COBOL code to ensure adherence to company standards and efficient use of system resources.
• Review, evaluate, and analyze software design and specifications;
• Work with the Quality Assurance team to determine if the application fit specifications and technical requirements;
• Identify and fix bugs, devise solutions to the problems;
• Maintain code quality, organization, and automatization;
• Maintain the developed software efficiently through a solid knowledge of the software lifecycle
• Understanding of SDLC automation concept such as continuous integration
• Everyday communication with US customer teams (requirements clarification, status update, issues etc.)
• Maintain comprehensive technical documentation, including code structure, user guides.
• Communicate effectively with cross-functional teams and stakeholders.
• Stay updated on new technologies and methodologies to ensure continuous improvement of the development process

Department/Project Description

Our client is a performance rights organization in the United States. It collects blanket license fees from businesses that use music, entitling those businesses to play or sync any songs from the client's repertoire of over 22.4 million musical works. On a regular basis, the client distributes the money to songwriters, composers, and music publishers as royalties to those members whose works have been performed.

We are looking for a Founding Engineer to join a fast-growing start-up developing a product for automated lead generation and recruitment outreach.  

Responsibilities: 

- Autonomously architect, prototype, & build the product from the ground up.

- Develop integrations with AI (e.g. Perplexity, OpenAI) & 3rd party API (e.g. CRMs).

- Leverage your prompt engineering skills to maximize the outcome.

- Horizontally work with founders in discussions on business & product topics.

Requirements: 

- 1+ years of experience in a SaaS/startup previously. 

- Senior-level engineer with 5+ years of software development experience. 
- Experience in RAG & AI agents development and prompt engineering.
- API development and integration experience.
- Database design and optimization (SQL).
- Development in cloud infrastructure (AWS/GCP/Azure).
- Patterns for asynchronous task processing (RabbitMQ, SQS, or similar).
- Experience with n8n/make will be a great plus.

- Authentic obsession with giving customers the best.
- Excellent verbal communication skills.

- Excellent English, strong B2 level minimum.

Job details:

• Full-time.
• Fully remote.
• Long-term.
• B2B contract.
• Start date — ideally ASAP / by mid-April.
• Also, you will get founding member equity % in addition to your fixed salary.

What else will you get:

- Learning how a startup grows.

- Direct impact on product and company strategy.

- Deliver value directly to paying B2B clients.

- Opportunity to build and lead a team and department.

- You will work with the most modern toolset (including Cursor in Agent mode).

The hiring process: 

• 45 min pre-screen interview with a recruitment manager
• 15-30 min call with the client
• a technical deep-dive interview, most likely with online coding (conducted by client)
• online call with the team or key team members

We are looking for a Founding Engineer to join a fast-growing start-up developing a product for automated lead generation and recruitment outreach.  

Responsibilities: 

- Autonomously architect, prototype, & build the product from the ground up.

- Develop integrations with AI (e.g. Perplexity, OpenAI) & 3rd party API (e.g. CRMs).

- Leverage your prompt engineering skills to maximize the outcome.

- Horizontally work with founders in discussions on business & product topics.

Requirements: 

- 1+ years of experience in a SaaS/startup previously. 

- Senior-level engineer with 5+ years of software development experience. 
- Experience in RAG & AI agents development and prompt engineering.
- API development and integration experience.
- Database design and optimization (SQL).
- Development in cloud infrastructure (AWS/GCP/Azure).
- Patterns for asynchronous task processing (RabbitMQ, SQS, or similar).
- Experience with n8n/make will be a great plus.

- Authentic obsession with giving customers the best.
- Excellent verbal communication skills.

- Excellent English, strong B2 level minimum.

Job details:

• Full-time.
• Fully remote.
• Long-term.
• B2B contract.
• Start date — ideally ASAP / by mid-April.
• Also, you will get founding member equity % in addition to your fixed salary.

What else will you get:

- Learning how a startup grows.

- Direct impact on product and company strategy.

- Deliver value directly to paying B2B clients.

- Opportunity to build and lead a team and department.

- You will work with the most modern toolset (including Cursor in Agent mode).

The hiring process: 

• 45 min pre-screen interview with a recruitment manager
• 15-30 min call with the client
• a technical deep-dive interview, most likely with online coding (conducted by client)
• online call with the team or key team members

Welcome to Drawer.AI!

- What we do: AI-driven workflows that let estimators pull quantities and costs from complex PDF drawing sets.  
- Stage: Seed-funded, revenue-generating, aiming for a Series A in 2026.  
- Why join now: Real customers are pushing our roadmap faster than our current front-end team can build.

We are looking for an AI/ML Engineer who will work at the intersection of LLMs, classical algorithms, and applied machine learning, focusing on designing and improving intelligent systems that solve complex real-world problems.

Key Responsibilities:

• Conduct extensive research, prioritize and analyze possible approaches to solving complex technical problems.
• Audit existing algorithms and improve them using LLM/ML approaches.
• Design and develop new solutions that combine LLMs with traditional algorithmic techniques.
   

Requirements:

• 5+ years of experience in AI, mathematical optimization, or a closely related field.
• Solid understanding of machine learning and deep learning concepts.
• Experience with neural networks for object classification, detection, and segmentation.
• Strong mathematical and statistical foundation (linear algebra, Euclidean geometry, probability).
• Strong expertise in algorithms and data structures (graph theory, computational geometry, mathematical optimization).
• Proficiency with deep learning frameworks such as TensorFlow, PyTorch, or equivalent.
• Proven experience writing custom algorithms and heuristics, and integrating them with ML approaches.
• Experience deploying models in production environments.
• Hands-on experience with AWS services (S3, Lambda, Step Functions, Bedrock).
• Experience building LLM-powered pipelines with LangChain.

Nice to have:

• Experience with graph neural networks (GNNs).
• Experience extracting and processing information from PDF and SVG files.
• Experience with Django, FastAPI.
• Track record of integrating LLMs into production products.
• Published research in any domain of AI.
• Relevant AI/ML certifications.
• Participation in hackathons or Kaggle competitions.
• Master’s or PhD in Computer Science or a related field.

Join our stellar team at Drawer.AI, where excellence meets opportunity! Experience the exceptional; enjoy a competitive salary and career advancement and the outstanding work environment we take pride in. Elevate your professional journey with us – because we believe in creating success together. Build a better future with us!

• Project Description:

  Learning Management and Development enables each member of the company to access various training services, such as trainer-led courses, upskilling programs for Direct and Line Managers, webinars, foreign language lessons, training paths & sets, internship programs, self-learning libraries, external providers (conferences and certifications), and other training services.

• Responsibilities:

  • Organization/help any events concerned with training in location;
  • Ability for accurate work in internal management systems and tools;
  • Training modules preparations (infrastructure, materials, invitations, certificates, problem solving etc.);
  • Introduction trainings (consulting, organization, closing in the system).
  • Process the Training plan (assure the accuracy of the forecast);
  • Cooperation with internal and external training providers;

• Mandatory Skills Description:

  Higher education;
  • Good communication skills;
  • Experience with databases;
  • Advanced PC user (MS Office, Outlook, Internet Explorer);
  • Great sense of responsibility with ability to work under pressure independently as well as in teams;
  • Strong attention to details and organization;
  • Self-starter and proactive approach to resolving

• Nice-to-Have Skills Description:

  Organization experience (internal events, daily activities related with trainings)

• Languages:
  • English: B2 Upper Intermediate

Imagine joining a startup at the very beginning - founded by Ukrainians in Silicon Valley, backed by global investors, building AI that's rewriting how a $7 trillion industry works. Superagent AI is creating the world's first autonomous AI sales agent - an AI that listens, learns, and coaches humans to sell better than ever before. 

We're already working with top U.S. insurance networks - and we're just getting started.

Now, we're seeking one exceptional individual - sharp, curious, and hardworking - who wants to build, learn, and grow directly alongside the founders.

The Role: AI Prompt Engineer / Research Assistant

You'll be part of the small, core team helping our AI learn to think and communicate like a top-performing human. You'll experiment, build, and constantly iterate.

Your work will be seen and used by real customers - in the U.S., Europe, and beyond.

You will:

• Write and optimize prompts that guide how our AI "thinks" and "talks";
• Design realistic conversations between AI and humans (sales, coaching, empathy, etc.);
• Analyze AI outputs and refine for accuracy, tone, and compliance;
• Research and test different sales, communication, and behavior models;
• Collaborate with founders and engineers to improve product intelligence.
   

This is a creative, technical, and analytical role - perfect for someone who lives and breathes AI and wants to grow fast.

What We're Looking For

We don't care about your degree. We care about your hunger, brains, and curiosity.

You might be the right person if you:

• Write and think fluently in English;
• Fluent in optimizing your workflows with Claude Code or Cursor/Antigravity/etc;
• Spend hours experimenting with ChatGPT, Perplexity, Gemini, Grok, and other AI models & tools;
• Love learning, figuring out how things work, and pushing limits;
• Have a mix of logic + creativity - analytical and human at the same time;
• Thrive in fast, messy, startup environments where you get stuff done.
   

Bonus points for:

• Side projects (anything that shows initiative);
• Experience in linguistics, psychology, computer science, or sales;

• Understanding of how people communicate, persuade, or make decisions.
   

   

Why You'll Love It Here

Real mentorship - You'll work directly with our founders:

• Vlada Lotkina (Wharton MBA, 8-figure exit, ex-BCG & Dell Strategy)
• Vadym Shashkov (AI engineer, YC alum, built 70+ mid-large-sized projects and managed large teams)
   

You'll learn more in 3 months here than in 3 years anywhere else.

• Global exposure - Build AI that's being deployed across the U.S. and Europe.
• Ownership & trust - You'll make real decisions, not PowerPoints.
• Career rocketship - Grow from "junior" to "indispensable".
• Flexibility - Work remotely, but think globally.
• Competitive pay with performance-based bonuses.

What Makes This Special

This is not a "prompt engineering internship". This is your chance to help train the mind of an AI that will transform how millions of people work. 

If you're the type who's constantly curious, relentlessly improving, and deeply proud of your craft, you'll thrive here.

COMPANY

Arcyn is a freshly funded seed stage startup. We’re creating an AI-powered compliance checker for architectural design — an Autodesk Revit plugin that automatically checks designs against regulations as they're being created. Architects get instant feedback on violations as they design in Revit, instead of waiting weeks for permit reviewers to tell them what's wrong.

We’ve just closed pre-seed round and are building core technical team. We’re now a team of 4 with a track record of building complex technical products, and we're looking for a strong AI engineer who's comfortable testing hypotheses and working across different frameworks. This is a chance to join at the ground floor, shape product architecture and solve genuinely hard AI problems.

----

In this role, you'll architect AI systems from scratch and own the full development cycle, there's plenty of room for experimentation and rapid iteration. We're seeking a highly skilled AI Engineer with strong experience in orchestrating multi-step LLM workflows, automated code generation, and compliance logic formalization.

RESPONSIBILITIES: 
• Design and maintain modular, multi-step AI workflows for compliance automation. 
• Integrate multiple LLM providers (e.g., OpenAI, Anthropic, Perplexity) into a cohesive orchestration pipeline. 
• Build cost-optimized batch processing and intelligent API request strategies. 
• Translate complex regulations into structured, machine-executable logic. 
• Develop and validate automatically generated code to ensure correctness, safety, and performance. 
• Collaborate with domain experts to refine logic interpretation and edge case handling. 

• Maintain high-quality, well-structured Python codebases with clear separation of concerns. 

REQUIREMENTS  
• 5+ years of professional software engineering experience. 
• Strong Python skills, including experience writing production-grade, modular code. 
• Proven track record building multi-step LLM workflows (LangChain, LangGraph, or similar). 
• Experience in structured code generation and validation. 
• Strong debugging skills and comfort working with complex, evolving systems. 

   NICE TO HAVEs: 
   • Experience with compliance automation, technical regulations, or domain-specific rule translation. 
   • Familiarity with Pydantic models or other type-safe data management frameworks. 
   • Background in developer tooling or systems requiring high reliability and reproducibility. 
   • Experience optimizing LLM API usage for both cost and speed. 

WE OFFER:

• B2B set-up via SP account
• Full-time remote role aligned with EEST
• Be part of the team shaping a new AI product at an early stage. 
• Freedom to architect solutions using the best tools for the job. 
• Collaboration with a multidisciplinary, innovation-driven team. 
• Flexible work arrangements and competitive compensation.

We are looking for a Machine Learning Engineer to design and implement intelligent systems that power personalized digital experiences across connected devices and mobile applications.

This role is ideal for someone who thrives at the intersection of ML models, data pipelines, and product integration. You will collaborate closely with backend engineers, data scientists, and product managers to bring ML-driven features into production and continuously optimize them based on real-world usage.

Responsibilities:

• Design, train, and deploy machine learning models for use cases such as personalization, recommendations, and visual analysis;
• Build and maintain scalable, production-grade data pipelines (batch and real-time);
• Collaborate with product and engineering teams to translate product ideas into ML-powered features;
• Implement model observability, monitoring, and retraining workflows;
• Optimize inference performance and model serving in resource-constrained environments (e.g., edge or mobile);
• Contribute to the architecture of a modern ML platform within a cloud-native microservices environment;

• Work with backend teams to expose model outputs via APIs and integrate them into customer-facing experiences.

   

Requirements:

• 3+ years of experience in applied machine learning or data science;
• Strong knowledge of:
  • Supervised learning, recommendation systems, or computer vision;
  • Python and ML libraries such as TensorFlow, PyTorch, scikit-learn;
  • Building, deploying, and maintaining ML models in production.
• Familiarity with:
  • MLOps tools (e.g., MLflow, TFX, Airflow, Vertex AI);
  • Data pipelines and messaging systems (e.g., Kafka, BigQuery, dbt);
  • Model serving frameworks (e.g., FastAPI, TensorFlow Serving, TorchServe, ONNX);
• Comfortable collaborating with product, engineering, and analytics teams;
• Experience with cloud platforms (GCP, AWS, or Azure) and container-based deployments;
• Bonus: Experience with edge AI, mobile ML, or video/image processing pipelines.

We Offer:

• Remote work and flexible working hours.
• Legal support.
• Paid sick leaves.
• Paid vacations.
• Medical insurance. 
• Free English classes.

Senior Computer Vision Engineer

About Us

We are a technology company with roots in algorithmic trading, where we built real-time systems that process massive, noisy data streams with zero tolerance for delay.
We are now applying this engineering DNA to a new MilTech division — an AI battlefield intelligence platform, from petabyte-scale video annotation to real-time inference on custom hardware at command posts.
We have exclusive data partnerships with frontline Ukrainian military units, an operational annotation pipeline with active learning and a trained detection model (v1).
The infrastructure is built and the data is flowing — we need experienced CV engineers to push the models forward.

The Role

We are looking for a Senior CV Engineer to join the ML team and focus on developing, training, and optimizing computer vision and vision-language models for battlefield target detection, classification, and contextual intelligence.

What You Will Do

Model Development & Training
- Train and iterate on detection, classification, tracking, and segmentation models on real combat footage
- Experiment with vision-language models (VLMs) for scene understanding and contextual reasoning
- Run distributed multi-GPU training experiments and manage the experiment lifecycle
- Improve model accuracy through architecture selection, hyperparameter tuning, data augmentation, and training strategy
- Contribute to the active learning loop: analyze confidence distributions, refine auto-labeling thresholds, identify hard cases for human review

Battlefield Contextual Intelligence
- Develop area-level temporal analysis: change detection across sequential overflights, environmental cue recognition
- Build sequence-aware model architectures (temporal attention, video transformers) for multi-frame reasoning
- Collaborate with military subject-matter experts to encode operator knowledge into model features and evaluation criteria

Model Optimization & Deployment
- Quantize and optimize models for deployment on custom AIPU inference hardware (INT8, mixed-precision, quantization-aware training)
- Validate that optimized models meet accuracy targets against gold-set benchmarks
- Support multi-stream inference validation at command post scale (100+ concurrent streams per rack)

Data & Annotation Quality
- Work with the annotation team to refine the labeling ontology and quality control criteria
- Analyze model errors to identify gaps in training data and drive targeted data collection
- Evaluate dataset diversity and coverage using embedding-based curation tools

What We Are Looking For

Must Have
- 4+ years in computer vision and deep learning, with production model deployments
- Strong PyTorch proficiency, including distributed training (DDP/FSDP)
- Hands-on experience with object detection pipelines (YOLO family, RT-DETR, or similar)
- Model optimization experience: quantization, pruning, or export to inference runtimes (ONNX, TensorRT, or similar)
- Solid understanding of training methodology: experiment design, ablation studies, metrics analysis
- Python as primary language; clean, production-grade code

Strong Plus
- Experience with vision-language models (CLIP, Florence, PaliGemma, or similar)
- Video understanding or temporal model architectures
- UAV / drone / robotics domain experience
- MilTech or defense-related work
- Change detection or remote sensing experience
- Experience with active learning or data-centric ML workflows
- C++ for performance-critical components

Tech Stack

- Training: PyTorch, distributed training (DDP/FSDP)
- Data processing: Ray Data
- Data curation: FiftyOne, embedding-based selection
- Annotation: CVAT with pre-annotation and active learning
- Experiment tracking: MLflow
- Inference: Custom AIPU hardware (model export via ONNX + quantization)
- Infrastructure: Kubernetes, on-prem GPU cluster (NVIDIA L40S)
- Storage: S3-compatible object storage (Ceph)

What We Offer

- A role focused on what you do best — building and improving CV models, not setting up infrastructure
- Real combat footage dataset — petabyte-scale, operationally relevant, impossible to replicate
- Dedicated on-prem GPU resources — no cloud queues or budget negotiations for compute
- Direct collaboration with military operators whose domain expertise shapes the models
- Competitive salary
- Stock options
 

We are building an AI-driven SDLC automation platform leveraging AWS Bedrock, knowledge bases, domain agents, and tool-based orchestration. We are looking for a Senior AI Engineer to design and implement the AI architecture, including RAG pipelines, agent systems, tool-calling mechanisms (MCP-style architectures), model evaluation, and guardrails. This role requires real production GenAI experience, not experimentation.

Requirements: 

• 6+ years software engineering experience
• 3+ years hands-on ML / AI engineering experience
• Strong Python (mandatory)
• Proven production experience with LLM systems
• Experience with AWS Bedrock
• Experience designing tool-calling LLM systems (MCP or equivalent architecture)
• Experience integrating external APIs as agent tools
• Experience building REST services (FastAPI or similar)
• Experience with vector databases (OpenSearch, Pinecone, etc.)
• Experience implementing evaluation frameworks for LLM quality
• Experience mitigating hallucinations and prompt instability
• Experience integrating with GitHub and JIRA APIs
• Production experience beyond notebooks or PoCs

• Deep understanding of:

  - RAG architecture

  - Embeddings

  - Chunking strategies

  - Retrieval optimization

• Strong understanding of:

  - Token economics

  - Context window constraints

  - Cost-performance tradeoffs

Responsibilities: 

• Implement RAG pipelines on AWS Bedrock
• Design knowledge ingestion pipelines (JIRA, GitHub, Confluence, S3)
• Define chunking, embedding, and retrieval strategies
• Design vector storage and retrieval architecture
• Architect tool-calling agent systems (MCP or equivalent)

• Define when to use:

  - Direct API invocation

  - Lambda-based tools

  - MCP-based tool integration

  - Design and implement structured output agents

• Implement hallucination mitigation strategies
• Build evaluation pipelines for model quality and regression testing
• Optimize token usage and latency
• Define model routing strategies (cost vs quality)
• Implement guardrails and structured validation
• Work closely with DevOps to productionize AI services
• Mentor AI engineers and define AI engineering standards
• Define long-term GenAI roadmap and architecture patterns

What is in for You: 

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. 

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!

High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.

Automat-it is an all-in AWS Premier Partner and Managed Services Provider specializing in the startup ecosystem. With over 800 customers and 500+ AWS certifications, Automat-it brings hands-on expertise in AI, DevOps, and FinOps to empower fast-paced startups to grow, deliver & win. Our customers save significant time-to-market and optimize their cloud performance and costs.

We work across EMEA and the US, fueling innovation and solving complex challenges daily. Join us to grow your skills, shape bold ideas, and help build the future of tech.

We seek an experienced Senior AI Engineer to join our team. You will work hands-on with innovative startups' Data Science and R&D teams and be in charge of various projects. You will develop robust MLOps pipelines, create cutting-edge Generative AI solutions, implement the latest technologies, and ensure the customers’ success by overseeing the project from inception to completion.

📍 Work location - remote from Ukraine

If you are interested in this opportunity, please submit your CV in English.

Responsibilities

• Developing backend Generative AI solutions and POCs, utilizing RAG pipelines, agent-based systems, and LLM-powered services
• Taking existing ML or customer-provided code and adapting it for training, fine-tuning, and production deployment using PyTorch
• Developing and optimizing fine-tuning workflows, model evaluation, benchmarking, and inference optimization
• Provision of ML AWS resources and infrastructure primarily using managed and cloud-native services
• Developing ML-oriented CI/CD pipelines using GitHub Actions, Bitbucket, or similar tools
• Deploying Machine Learning models in production and ensuring they are observable and monitorable
• Collaborating with Solution Architects and DevOps teams on scalable and cost-efficient AI infrastructure
• Learning new skills and technologies quickly to stay up to date with rapidly evolving GenAI tools
• Using and writing Terraform libraries for infrastructure deployment
• Maintaining infrastructures and environments of all types, from dev to production
• Security monitoring and administration

Requirements

• Excellent customer-facing skills to understand and address client needs effectively
• Ability to design and implement cloud solutions and to build GenAI pipelines on AWS
• Experience with one or more large language model frameworks like OpenAI SDK, Amazon Bedrock, LangChain, and LlamaIndex
• Fluency in Python, a good understanding of Linux, and mandatory hands-on production experience with PyTorch
• Ability to understand tools used by data scientists and experience with building Generative AI applications beyond notebooks or demos
• Good understanding of supervised and unsupervised learning, and deep learning concepts
• Fluent written and verbal communication skills in English
• Ability to work hands-on, independently, and deliver under real project constraints
• Bachelor’s or Master’s degree in AI-related fields - an advantage
• Working knowledge of some Vector Databases (OpenSearch, Qdrant, Weaviate, LanceDB, etc.) - an advantage
• Experience with Docker and Kubernetes - an advantage
• Experience with Azure or GCP (DevOps/MLOps) for ML or GenAI workloads - an advantage
• ML certification (AWS ML Specialty or similar) - an advantage

Benefits

• Professional training and certifications covered by the company (AWS, FinOps, Kubernetes, etc.)
• International work environment
• Referral program – enjoy cooperation with your colleagues and get a bonus 
• Company events and social gatherings (happy hours, team events, knowledge sharing, etc.)
• English classes
• Soft skills training

Country-specific benefits will be discussed during the hiring process.

Automat-it is committed to fostering a workplace that promotes equal opportunities for all and believes that a diverse workforce is crucial to our success. Our recruitment decisions are based on your experience and skills, recognising the value you bring to our team.

N-iX is looking for a Lead AI Engineer to drive the design, evaluation, and evolution of AI-powered solutions. In this role, you will focus on building and scaling intelligent systems (including RAG-based and NLP-driven applications), while guiding clients through technical discovery, architecture decisions, and AI adoption strategies.

You will work closely with stakeholders to design and deliver AI-driven solutions that enhance business efficiency, streamline processes, and unlock value from data, while ensuring scalability, quality, and cost-effectiveness.

Key Responsibilities

• Design and implement AI-driven systems within Palantir Foundry AIP, including RAG pipelines, LLM-powered applications, and NLP workflows for document understanding and knowledge extraction
• Lead the end-to-end lifecycle of AI solutions, from data ingestion and embedding generation to retrieval, reasoning, and response generation
• Collaborate with AI/ML engineers to productionize models and LLM-based solutions, ensuring reliability, scalability, and performance
• Drive technical discovery and solution assessment, analyzing possible AI implementations, clarifying their architecture, and identifying risks and improvement opportunities
• Evaluate and optimize RAG pipelines, including retrieval quality, chunking strategies, embeddings, and hybrid search approaches
• Assess scalability, multilingual capabilities, and cost-performance trade-offs of AI systems
• Advise on AI architecture evolution, including platform choices, vendor dependencies, and potential migration paths
• Establish best practices for LLMOps / MLOps, including evaluation frameworks, prompt engineering, monitoring, and iterative improvement
• Ensure responsible AI practices, including data governance, security, and compliance considerations
• Mentor engineers and foster collaboration across AI, data, and product teams

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
• 6+ years of experience in software engineering, with strong exposure to AI/ML systems
• Hands-on experience with LLM-based applications, RAG pipelines, or NLP systems
• Experience building multimodal AI systems, including working with text, documents, images, and/or other data types
• Experience developing AI solutions for multiple languages, including handling multilingual data, prompts, and evaluation
• Strong proficiency in Python and experience with AI/ML frameworks and tooling
• Experience designing and deploying scalable AI systems in production environments
• Understanding of vector databases, embeddings, retrieval strategies, and hybrid search
• Experience with MLOps / LLMOps practices, including model lifecycle management, evaluation, and monitoring
• Ability to perform technical discovery and communicate complex AI concepts to both technical and non-technical stakeholders
• Strong leadership, communication, and stakeholder management skills
• English Upper-Intermediate +

Nice to Have

• Experience with Palantir Foundry
• Familiarity with distributed systems or large-scale data processing (e.g., Spark)

Who we are:

Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries. 

About the Product: 

Over the past few years Coro has received $175M in funding and is one of the fastest growing Cybersecurity companies in the world. The funding is primarily being used to enhance the Coro Cybersecurity SaaS platform and for additional headcount growth, as Coro continues to expand globally.   

Coro started in Tel-Aviv, Israel and is also headquartered in Chicago, IL with additional offices in New York, London, and remotely across the globe. As a global organization, Coro gives you the ability to work with people and teammates from around the world. 

Coro’s AI enabled Modular Cybersecurity Platform is the only one in the industry specifically designed to provide Mid-Market customers with scalable and affordable “enterprise grade” protection for all of their priority threat vectors. 

About the Role: 

This is a principal-level AI engineering role focused on driving the next generation of AI adoption across Coro — both within the product and across the organization.

You will take ownership of AI-driven initiatives end-to-end, shaping how engineering teams build, ship, and scale software using LLMs, agents, and intelligent tooling. The role is not about day-to-day coding, but about defining architecture, building workflows, and delivering impactful AI solutions that improve developer productivity and system quality.

You will work closely with DevEx, Core Engineering, Product, and R&D, helping standardize and scale AI usage across teams — moving from ad-hoc usage to a structured, high-impact AI-driven environment.

If you are looking for a role where you can combine technical leadership, ownership, and innovation, and influence how a global engineering organization adopts AI — this is the role for you.

Key Responsibilities: 
 

•  Build a shared vision with DevEx and Core Engineering leadership for AI-driven developer tooling, supporting development by prototyping agents and workflows while serving as a subject matter expert for internal R&D efficiency
• Work closely with Product and R&D stakeholders, taking full responsibility and ownership from conception to post-deployment of AI tools that automate and optimize the daily work of engineering teams
• Work in a modern CI/CD environment with a team of highly skilled developers, leveraging LLMs and agentic frameworks to redefine and improve the developer experience
• Spearhead the development of new internal features and AI agents — from automated code review to intelligent debugging tools — while owning the full development lifecycle
• Contribute to the overall technical strategy and roadmap of the internal platform, driving initiatives that use AI to improve developer velocity, code quality, and system reliability
• Promote a culture of innovation and continuous growth, encouraging the exploration of emerging AI technologies to solve complex engineering bottlenecks
• Continuously monitor developer feedback and internal productivity metrics to identify opportunities for optimization and further tool refinement

Our Stack: Java (Spring-based microservices), Golang, and Python services, running on Kubernetes (AWS EKS). We use Redis, MongoDB, SQL, OpenSearch, RabbitMQ,  AWS Lambda and additional cloud-native technologies. We encourage engineers to stay current with industry trends and emerging technologies to continuously evolve our platform

Required Competence and Skills:
 

• Proven experience working with AI/LLMs, agents, or AI-driven workflows in production environments
• 7+ years of experience building complex web applications and scalable backend systems
• Strong background in platform engineering, developer productivity, or internal tooling
• Ability to work closely with engineers, R&D leaders, and cross-functional stakeholders to define productivity goals and design AI-driven solutions
• Strong product and engineering judgment, with a clear understanding of how to build internal tools that create a smooth and frictionless developer experience
• Strong focus on quality, simplicity, and maintainability when designing solutions for complex engineering problems
• Hands-on experience with LLMs, automation, and AI-driven workflows, combined with an analytical, curious, and data-driven mindset
• Experience implementing AI solutions at an organizational level (not only in isolated projects)
• Strong collaboration and communication skills, with empathy for the challenges faced by modern engineering teams

Nice to have:
 

• Technical leadership experience in roles such as Architect, Tech Lead, or similar, especially in platform engineering or developer productivity areas
• A degree in Computer Science or a related field is a plus, but we are also open to exceptional candidates with strong practical experience

Why Us?

We provide 20 days of vacation leave per calendar year (plus official national holidays of a country you are based in).

We provide full accounting and legal support in all countries we operate.

We utilize a fully remote work model with a powerful workstation and co-working space in case you need it.

We offer a highly competitive package with yearly performance and compensation reviews.

We’re hiring RL Environments Engineers to design and build MLE/SWE environments that deliver high-quality, diverse tasks with minimal supervision. You will target a specific language model, meet a defined difficulty distribution, and deliver about one task every 10 hours. This is a remote contractor role with ≥4 hours overlap to PST and advanced English (C1/C2) required.

Responsibilities

• Design and build MLE/SWE environments and diverse tasks.
• Target a specified language model and satisfy the required difficulty distribution.
• Deliver ~1 task per 8-10 hours once onboarded.
• Edit tasks within 24 hours based on customer feedback.
• Onboard quickly and start delivering on day one with minimal supervision.
  
   

Requirements

What we’re looking for (must-haves)

• Strong Python (engineering-quality, not notebook-only).
• Hands-on LLM/GenAI work in production: you’ve shipped and operated real systems (not “wrapped an API and called it AI”).
• Strong product/engineering ownership: comfortable building, fixing, and scaling end-to-end pipelines.
• Docker + production mindset (debugging, reliability, iteration speed).
• ≥4 hours PST overlap and advanced English (C1/C2) for specs, reviews, and feedback.
• Ability to meet throughput expectations and respond quickly to feedback.
   

Strong signals (nice-to-have, big plus)

• Experience designing environments/tasks for RL and/or evaluations.
• Experience in high-stakes or regulated domains (e.g., healthcare, finance, fraud/risk, safety-critical systems).
• ML systems experience: CI/CD, monitoring, evaluation harnesses, MLOps, scalable pipelines.
• Systems depth: C++/Rust/Scala/Java, performance/infra optimization, distributed systems.
• Exposure to RL / bandits / agentic systems (not required, but a strong signal).
   

Not a fit if

• You’re primarily a prompt engineer without strong ML/engineering foundations.
• You’re a research-only / academic-only profile with little or no shipping/production ownership.
• You’ve only built in notebooks or rely heavily on managed AutoML tools.
  
   

Working Conditions

• Remote, independent contractor engagement.
   
• 40 hours/week - full time - need 4 hours overlap in the working hours with the team in Pacific time zone;
• Deliverables-driven; begin shipping on day one.

Conversion & relocation: Potential path to FTE and relocation to the Bay Area if performance and mutual fit align.
 

We're hiring Low-Level Engineers to design and build RL environments that teach LLMs kernel development, hardware optimization, and systems programming. The goal is to create realistic feedback loops where models learn to write high-performance code across GPU and CPU architectures.

This is a remote contractor role with ≥4 hours overlap to PST and advanced English (C1/C2) required.

Requirements

Minimal Qualifications

• Strong Python (engineering-quality, not notebook-only)
• Production mindset (debugging, reliability, iteration speed)
• Clear understanding of LLMs, their current limitations
• Ability to meet throughput expectations and respond quickly to feedback

You may be a good fit if one of the following applies

• Deep understanding of memory hierarchies (registers, L1/L2/shared memory, HBM, system RAM) and their performance implications
• Threading models, synchronization primitives, and concurrent programming (warps, thread blocks, barriers, atomics)
• Cache coherence, memory access patterns, coalescing, and bank conflicts
• JIT compilation frameworks (e.g., Triton, JAX/XLA, TorchInductor, Numba)
• AOT compilation and optimization passes (LLVM, MLIR, TVM)
• Compiler and kernel frameworks such as CUTLASS, BitBLAS, or JAX/Pallas
• Modern C++, including templates, concurrency, and build systems
• Assembly-level programming and low-level optimization across GPU and CPU architectures (e.g., x86, ARM, NVIDIA Hopper, NVIDIA Blackwell)
• Debugging and optimizing GPU kernels using CUDA and/or HIP/ROCm
• Developing PyTorch custom operators, backend extensions, or dispatcher integrations (e.g., ATen, TorchScript, or custom backends)
• Customizing, extending, or optimizing c, including distributed inference workflows
• GPU communication libraries and collectives, such as NVIDIA NCCL, AMD RCCL, MPI, or UCX
• Mixed-precision and low-precision kernels (e.g., FP16, BF16, FP8, INT8), including numerical stability and performance trade-offs