Python Backend Engineer (ML)

AppGreat is one of the fastest growing global IT companies, supporting the highest tech organizations in the world with 6 offices: 1 in Sofia, 1 in Skopje, 1 in Bucharest, 1 in Tel Aviv, 1 in Chisinau and 1 in Warsaw.

We are working with top talents and highly experienced management to ensure the world's leading technology companies meet all the business challenges that the future holds.

We are AppGreat! We are a young and ambitious company like no other!

WHY JOIN OUR DREAM TEAM?

The most important part of AppGreat is the team. From our founders to the last person, we are committed to creating a pleasant environment and a place where everybody feels like they belong.

We invest in them in any way we can, starting from the amazing atmosphere in the office, unique benefits and career growth opportunities.

We are seeking a skilled Python Back-end Engineer to join our team and productize cutting-edge ML/AI models in the Legal domain and audio processing more broadly. This role requires solid Python backend engineering experience and strong Machine Learning experience, with the ability to design, develop, and deploy production-grade ML systems. Part of this role includes speech engineering — prior ASR/speech experience is not a must, but a willingness to learn and grow into this domain is essential. LLM AI experience, including agentic flows, LiteLLM, CrewAI, AgentCore, AWS Bedrock, and similar tools, is considered a bonus and is not a must-have requirement.

YOUR MISSION:

• Integrate various AI/LLMs into production solutions (including training/finetuning existing models);
• Optimize ML models for inference, specifically focusing on GPU acceleration;
• Build and maintain CI/CD pipelines (e.g., CircleCI) for deployment, unit testing, and integration testing.
• Own and ensure the end-to-end automation testing of deployed models.
• Support and extend the company's existing speech solutions (including 3rd-party ASR integrations and self-hosted ML models).
• Productize ML/ASR models prepared by the research team (Nо training ASR models from scratch).

WHAT YOU WILL BRING TO THE COMPANY:

• 4+ years of experience developing, wrapping, optimizing, and deploying modern ML/AI models in production.
• Develop/wrap, optimize, and deploy modern ML/ASR models in production environments (ASR, SpeakerID, RoleID, LangID, Acoustic events)
• Optimize models for inference, including GPU acceleration
• Productize ML models prepared by research teams and integrate them into production systems
• Understand model evaluation, performance trade-offs, and production monitoring
• Strong experience with Python backend development
• Build production-grade backend services, APIs, and microservices around ML models
• Experience with Python, Docker, gRPC, websockets, and microservices
• Build reliable, maintainable, and testable backend components
• Integrate ML services into larger production systems
• Experience with a cloud provider (AWS/GCP/Azure — we work with AWS)
• Work across multiple accounts/regions. ECR, EC2, ECS, CloudWatch.
• Deploy API Gateway, DynamoDB, Lambda and other resources via serverless and terraform across environments
• Build and maintain CI/CD pipelines (e.g. CircleCI or others) for deployment, unit testing, and integration testing.
• Ensure end-to-end automation testing of deployed models.

NICE TO HAVE / ADVANTAGE:

• Experience building and productizing agentic flows and AI-driven solutions
• Experience with frameworks and platforms such as CrewAI, AWS Bedrock, AgentCore, LiteLLM
• Experience integrating various LLMs into production solutions, including training/finetuning of existing LLM models
• Familiarity with LLM orchestration, RAG, prompt pipelines, tool usage, or AI agents.

*Prior ASR/speech experience is not a must — but since this will be part of the job, a genuine willingness to learn and grow into this domain is essential. In this area you will:

• Support and extend our existing speech solutions, including 3rd party ASR integrations and self-hosted ML models (end-to-end neural networks, NVIDIA Nemo ASR models, speaker feature extractors, LangID, acoustic events models, etc.)
• Productize ML/ASR models prepared by our research team (training ASR models from scratch is not required).
• Experience with real-time / streaming systems and low-latency processing (e.g. streaming pipelines, live sessions)
• Perform audio signal processing, working with audio files, audio streams, and audio buffers using tools like FFmpeg and other audio-processing toolkits.
• Measure and improve key ASR and SpeakerID metrics such as WER, latency, F1 score, EER, and DER.

OUR COMMITMENT TO YOU:

• Attractive remuneration package.
• Working style - Remote.
• Flexible Working Hours: We care about results, not when you clock in, depending on the team working schedule.
• Comprehensive Private Medical Insurance: Your health matters to us (UNIQA) / Medical Subscription Regina Maria (Premium Package).
• Annual leave starts with 20 days up to 25 days (depending on the relevant experience).
• Plus an extra day off to celebrate your birthday 🎉.
• Multisport Card: Stay active with a subsidized membership, courtesy of AppGreat.
• Monthly Food Vouchers.
• eMAG birthday gift voucher: A little extra something to celebrate your special day
• Childbirth gift: A thoughtful gift to support and celebrate one of life’s most important moments
• Team Events & Offsites: Regular team buildings and company events to keep the good vibes going.
• Learning & Development: Access to training programs to boost your skills and career.
• Career Growth Opportunities: Grow with a fast-scaling, innovation-driven company.
• Supportive Culture: Work with a young, motivated, and close-knit team.

We believe great work starts with great people. If this feels like the right place for you, we’d love to connect.

We appreciate every application we receive. Please note that only candidates selected for the next stage of the recruitment process will be contacted. If your profile matches the role, our Talent Acquisition team will reach out to you directly.