ML Engineer – Applied AI

This is a fully remote position, open to applicants in Ukraine.

📋 Description

• Design and Build AI Features: Create and implement robust classical machine learning and generative AI solutions, achieving an optimal balance between autonomous agent-based architectures and deterministic pipelines.

• Evaluation: Establish and maintain evaluation frameworks to assess AI quality, reliability, safety, and business impact prior to and following deployment.

• Integration & Deployment: Collaborate closely with full-stack developers and DevOps to effectively incorporate AI functionalities into client web and mobile applications using serverless architecture (e.g., AWS Lambda) or API endpoints.

• Production Optimization: Enhance prompts, system instructions, and chunking strategies to ensure a balance of accuracy, latency, token usage, and data privacy.

• Traditional Predictive Analytics: Clean and process unstructured or historical client data to train and fine-tune custom algorithms for specific business challenges (such as forecasting, classification, or anomaly detection).

• Collaboration & Communication: Actively engage in client discovery sessions, translate vague business requirements into actionable technical scopes, and demonstrate prototypes directly to stakeholder teams.

• Uphold Engineering Excellence: Participate in constructive code reviews, implement stringent validation patterns to test AI outputs, and contribute templates or runbooks to our internal AI knowledge base.

⛳️ Requirements

• Proven Experience: Over 3 years of experience in software engineering with a strong emphasis on machine learning and natural language processing.

• Mastery of LLM & Generative AI: Comprehensive understanding of contemporary LLM architectures, context window mechanics, semantic search techniques, and the limitations of generative systems. Ability to discern when a deterministic solution is preferable to an LLM or agent-based approach.

• Production Experience: Demonstrated experience in building and operating production AI systems, including monitoring, evaluation, debugging, and iterative enhancements.

• Evaluation Expertise: Knowledge of evaluation methodologies for LLM-based systems, including retrieval quality, hallucination detection, and task-specific performance measurement. Capacity to evaluate trade-offs between quality, latency, cost, reliability, and engineering complexity.

• Proficiency in Python & SQL: Exceptional skills in Python programming and the ability to efficiently query, clean, and organize data.

• Cloud Infrastructure Experience: Practical experience in deploying machine learning or API services within cloud environments, preferably AWS.

• Ownership Mindset: Comfortable taking responsibility for ambiguous problems from initial exploration through production deployment and ongoing support.

• Execution from Ambiguity: Capable of adapting to a completely new industry vertical, comprehending its data constraints, and developing a working proof-of-concept within a few weeks.

• The "Product Engineer" Perspective: Enthusiasm for delivering products and understanding the business value behind what is being built, not just the technical aspects.

• Communication Skills: Fluent in written and spoken English. Comfortable engaging with client stakeholders and simplifying technical workflows into clear concepts.

• Adaptability: Willingness to experiment with and assess rapidly emerging AI development tools, models, and frameworks.

• Educational Background: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field (or equivalent practical experience).

🏝️ Benefits

• Annual paid vacation: 20 days off per year during the first 3 years, increasing to 25 days in subsequent years.

• Paid sick leave, 10 national holidays, and 2 company days off.

• Well-being budget.

• Maternity/paternity leave.

• Reimbursement for professional development courses and certifications (up to 100% with Manager's approval).

• Hardware provided based on business needs.

• Strong positive engineering culture with a close-knit team of professionals who have a good sense of humor.