Akvelon

🌎 Akvelon is a known USA company, with offices in places like Seattle, Mexico, Ukraine, Poland, and Serbia. Our company is an official vendor of Microsoft and Google. Our clients also include Amazon, Evernote, Intel, HP, Reddit, Pinterest, AT&T, T-Mobile, Starbucks, and LinkedIn. To work with Akvelon means to be connected with the best and brightest engineering teams from around the globe and working with an actual technology stack building Enterprise, CRM, LOB, Cloud, AI and Machine Learning, Cross-Platform, Mobile, and other types of applications customized to the client’s needs and processes.

We are looking for a skilled MLOps Engineer with expertise in building and optimizing data pipelines, deploying models, processing large datasets, and managing infrastructure for machine learning applications. The ideal candidate will have a strong background in data engineering and hands-on experience in Google Cloud Platform (GCP), including Vertex AI, Kubeflow, BigQuery, and Cloud Storage.

Responsibilities:

• Develop and maintain ML pipelines for data ingestion, processing, and model inference, focusing on large-scale structured and unstructured data.
• Leverage GCP services (Vertex AI, Kubeflow, BigQuery, Cloud Storage, etc.) to build scalable and efficient ML infrastructure.
• Deploy deep learning models for both real-time inference and batch processing using tools like Vertex AI endpoints, Nvidia Triton, ONNX, and Dataflow.
• Implement ETL processes to clean, transform, and optimize data pipelines for ML applications.
• Manage large-scale text data, including preprocessing, document segmentation, and feature extraction.
• Collaborate with ML engineers and data scientists to curate high-quality datasets and optimize data workflows.
• Optimize performance of data pipelines and storage solutions to handle increasing data complexity and volume.
• Ensure automation and monitoring of data pipelines for reliability and efficiency.

• Document processes and best practices for pipeline architectures and data management.

   

Requirements:

• 4+ years of experience in MLOps/ML.
• Strong knowledge of Python and SQL.
• Hands-on experience with GCP services: Vertex AI, Kubeflow, BigQuery, Dataflow, and Cloud Storage.
• Experience in machine learning model deployments and pipelines.
• Familiarity with workflow orchestration tools (e.g., Kubeflow, Airflow, Cloud Composer).
• Strong understanding of ETL processes, data integration, and database management.

• Ability to work independently and overlap with EST time zone until at least 2 PM EST.

   

Nice to have:

• Experience with NLP and text processing libraries (e.g., NLTK, SpaCy, Regex).
• Familiarity with LLM ecosystem tools (e.g., LangChain, Embeddings, Vector DBs).

• Experience with GPU-based ML workloads and cloud deployment tools like Cloud Run and Kubernetes.

   

Working conditions and benefits:

• Paid vacation, sick leave (without sickness list)
• Official state holidays — 11 days considered public holidays
• Professional growth while attending challenging projects and the possibility to switch your role, master new technologies and skills with company support
• Flexible working schedule: 8 hours per day, 40 hours per week
• Personal Career Development Plan (CDP)
• Employee support program (Discount, Care, Health, Legal compensation)
• Paid external training, conferences, and professional certification that meets the company’s business goals
• Internal workshops & seminars
• Corporate library (Paper/E-books) and internal English classes

This is an exciting opportunity to contribute to ML infrastructure in the financial services domain while working with a cutting-edge tech stack. 🚀

🌎 Akvelon is a known USA company, with offices in places like Seattle, Mexico, Ukraine, Poland, and Serbia. Our company is an official vendor of Microsoft and Google. Our clients also include Amazon, Evernote, Intel, HP, Reddit, Pinterest, AT&T, T-Mobile, Starbucks, and LinkedIn. To work with Akvelon means to be connected with the best and brightest engineering teams from around the globe and working with an actual technology stack building Enterprise, CRM, LOB, Cloud, AI and Machine Learning, Cross-Platform, Mobile, and other types of applications customized to the client’s needs and processes.

We are looking for a Machine Learning Engineer to design and implement advanced models for multi-document understanding and summarization systems. This role involves developing innovative natural language processing solutions to tackle complex, greenfield business challenges with real-world impact.

The ideal candidate combines deep expertise in Natural Language Processing and Large Language Models, with strong coding and ML experimentation skills. The candidate should be able to design smart, automated AI workflows, work with modern ML tools, and build systems that can analyze and summarize information from many documents.

Responsibilities:

• Drive research ideas from first-principles conceptualization to practical realization.
• Collaborate with engineers to design and implement solutions that balance theoretical elegance with practical constraints.
• Develop innovative strategies for creating, collecting, and assessing high-quality datasets, including synthetic data generation.
• Design robust evaluation techniques and benchmarks for assessing diverse product properties.
• Conduct experiments to evaluate new methodologies and their impact on product outcomes.
• Stay up-to-date with the latest machine learning research to inform and guide model development.
• Research, train, evaluate, and improve machine learning models for document understanding, summarization, multi-document Q/A and multi-document summarization.
• Hands-on experience with modern NLP techniques, LLMs, prompt engineering and agentic workflows.
• Analyze data to uncover patterns, correlations, and opportunities for improvement.
• Conduct applied research to develop and launch models and/or agentic workflows that enhance strategic products.

• Communicate complex findings and research results through clear, concise, and compelling explanations, tailored to both technical and non-technical audiences, to drive understanding and collaboration.

   

Requirements:

• Ability to design and execute experiments, analyze results, and refine methods for optimal performance.
• Expert knowledge of ML fundamentals including feature engineering, model selection, and evaluation metrics.
• Proven ability to design and evaluate machine learning models, benchmarks, and experiments.
• Strong coding skills in Python and experience with NLP and ML frameworks.
• Experience with ML pipelines.
• Stay current with the latest research in AI, NLP and LLMs.
• Expertise in designing and implementing end-to-end ML systems.
• 4+ years of industry experience building production NLP/ML systems.
• Strong communication and independence skills.

• Working with daily overlap till 8 pm CET (2 pm EST).

   

Nice to have:

• Databases and Fatawarehouses experience.
• Experience with ETL and Data Integration.

• Finance and Investing Domain Knowledge

   

Working conditions and benefits:

• Paid vacation, sick leave (without sickness list)
• Official state holidays — 11 days considered public holidays
• Professional growth while attending challenging projects and the possibility to switch your role, master new technologies and skills with company support
• Flexible working schedule: 8 hours per day, 40 hours per week
• Personal Career Development Plan (CDP)
• Employee support program (Discount, Care, Health, Legal compensation)
• Paid external training, conferences, and professional certification that meets the company’s business goals
• Internal workshops & seminars
• Corporate library (Paper/E-books) and internal English classes

Ready to take the next step? Apply now!