Member of Technical Staff, Machine Learning

BJAK

Member of Technical Staff focusing on improving machine learning components for AI-native applications. Collaborate with teams to build reliable, production-grade ML systems in Portugal.

Posted 7/19/2026full-timeRemote • 🇵🇹 PortugalLeadWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates strong foundations in machine learning and modern neural architectures, with hands-on experience in training, fine-tuning, and deploying ML models. Capable of building and maintaining data pipelines while iterating on improvements based on user feedback under production constraints.

Highest-signal resume keywords

Machine Learning FoundationsNeural Architecture ExpertiseModel Training and Fine-TuningProduction-Quality Code WritingData Pipeline Development

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Machine LearningNeural NetworksModel EvaluationModel DeploymentData Pipeline ManagementDebuggingPerformance OptimizationIterative ImprovementSynthetic Data HandlingProduction Constraints Management

Soft Skills

CuriosityCoachabilityAdaptabilityOwnershipProblem-Solving

Industry Keywords

Real-World DataSynthetic DataUser FeedbackLatencyCost ManagementReliabilitySafety

About the role

Key responsibilities & impact

Build and improve ML components across data, training, evaluation, and inference.
Fine-tune and adapt models as part of larger production systems.
Implement evaluation and testing to understand model behavior.
Help build and maintain data pipelines for real-world and synthetic data.
Debug model issues, performance problems, and production incidents.
Ship improvements iteratively and learn from real user feedback.
Work closely with senior ML engineers and product teams.
Work under real production constraints: latency, cost, reliability, and safety

Requirements

What you’ll need

Strong foundations in machine learning and modern neural architectures.
Some hands-on experience training, fine-tuning, or deploying ML models.
Comfortable writing production-quality code and learning new tools quickly.
Curious, coachable, and eager to learn from real systems in production.
Able to work through ambiguity with guidance and grow ownership over time.
Bias toward shipping, iteration, and continuous improvement.

Benefits

Comp & perks

• • • • • • • • • • • • • • • • • • • • • • •