Dive deeper. Aim higher.
At Abysalto, that’s not just a motto — it’s how we work. We build serious tech for a variety of clients, but we keep things simple, fast, and focused. We’re a team driven by determination, expertise, and courage — and we’re looking for someone who shares that mindset. Someone ready to take ownership, solve real challenges, and make an impact where it matters. Ready to dive in? Join us as a Machine Learning Engineer!
🔷What will you do?
- Research, train, finetune, prototype, and production-ise AI models; from LLMs, custom NLP and classical ML models (e.g., LSTM, XGBoost, Random Forest), to vision and multimodal models (e.g., OpenCV, object detection, YOLO, VLMs)
- Build and maintain RAG pipelines using vector databases (FAISS, Pinecone, Milvus, etc.)
- Fine-tune and optimize models with PEFT/LoRA, quantization, and efficient inference engines (vLLM, llama.cpp)
- Evaluate model performance with custom benchmarks; iterate based on business KPIs and user feedback
- Package and deploy models through Docker/Kubernetes and CI/CD pipelines, working closely with DevOps and backend developers
- Collaborate with backend, front-end, and product teams to translate real-world problems into AI solutions
- Document your approach, share learnings, and champion best practices in MLOps and prompt engineering
- Contribute ideas on architecture, MLOps best practices, and new AI capabilities that can delight our customers
- Take ownership of your work, from concept to deployment — and refine it based on real-world feedback
🔷What do we expect from you?
- 1-3 years of hands-on Python for ML/AI (NumPy, pandas, scikit-learn, etc.)
- Production experience with PyTorch or TensorFlow and the Hugging Face Transformers ecosystem
- Familiarity with modern LLM inference tooling (vLLM, llama.cpp, TGI, Triton) and GPU workflows
- Demonstrated success building RAG systems end-to-end (data ingestion, embedding generation, retrieval, prompting)
- Practical know-how of PEFT/LoRA fine-tuning and training of transformers, BERT-style or embedding models
- Solid understanding of NLP tasks: NER, summarization, semantic search, vector similarity
- Comfortable with Git, Docker, and at least one cloud platform (AWS, Azure, or GCP)
- Clear, concise communication in English and a collaborative, curiosity-driven mindset
🔶Nice-to-haves
- Computer-vision hands-on exp (OpenCV, OCR, object detection/segmentation)
- Deep optimization techniques: quantization, KV-cache reuse, GPU offloading
- Experience designing or consuming Knowledge Graphs (Neo4j, RDF/SPARQL)
- Prompt-engineering tricks for LLMs (system vs. user roles, chain-of-thought, few-shot, etc.)
- Familiarity with MLflow, Weights & Biases, or similar MLOps platforms
🔷What do we offer?
- A key role in a high-growth area of our company
- Supportive environment for both tech and leadership growth, training, conferences, 1-on-1 mentorship
- Modern tech setup - high-performance hardware, ergonomic workstations (Aeron chairs), and access to GPU compute
- Flexible working hours with a hybrid work option
- Agile workflows with SCRUM methodology and a strong engineering culture
- All perks and benefits can be found on our career page
- A chance to build products that make millions of everyday interactions smarter and simpler
We solve complex technological challenges in order to simplify and improve everyday lives of millions of people. Our goal is to become a leader in the software industry, recognized for excellence and quality.
If you’re ready to lead what’s next, send us your CV and a few words on how you help teams succeed.
Apply via the link below.
We look forward to meeting you!