Machine Learning Engineer

UltraFix Appliance Repair, LLC

. Analyze existing data structures and assess data quality .

Posted 10/12/2026full-timeBaku • AzerbaijanMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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

Demonstrates expertise in Data Science and Machine Learning, with strong proficiency in Python and experience in building data parsing pipelines, feature engineering, and model optimization. Familiarity with privacy regulations and advanced data analysis techniques is essential.

Highest-signal resume keywords

Python ProficiencyData Science ExperienceMachine Learning Model DevelopmentSQL Query OptimizationData Quality Assessment

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonPandasNumPyScikit-learnTensorFlowPyTorchSQLFeature EngineeringModel EvaluationAnomaly Detection

Soft Skills

Advanced English

Tools & Technologies

REST APIsGRPCDockerAirflowKubeflowSparkDatabricks

Industry Keywords

AdtechMartechCDPCRMLookalike SegmentationRecommender SystemsFraud Detection

Tech Stack

Tools & technologies

AirflowDockerGRPCNumpyPandasPythonPyTorchScikit-LearnSparkSQLTensorflow

About the role

Key responsibilities & impact

Analyze existing data structures and assess data quality
Build data parsing and entity extraction pipelines to enrich customer profiles
Apply normalization and masking in accordance with privacy regulations
Build probabilistic models for extracting demographic and behavioral attributes using supervised/weak supervision, calibration, and confidence scoring
Write model results to a feature store
Identify data quality issues and propose improvement mechanisms
Perform feature engineering and model selection
Develop ML models for anomaly and pattern detection
Evaluate and optimize model performance
Build lookalike audience logic using embeddings, nearest neighbors, gradient boosting, and deep-learning models
Find similar users from seed audiences, size segments, and keep them updated

Requirements

What you’ll need

Bachelor's degree in MIS, Informatics, Computer Science, Computer Engineering, Mathematics or a related field
Strong proficiency in Python, including Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch
Minimum 3+ years of experience in Data Science or Machine Learning
Python with Pandas, NumPy, Scikit-learn, and at least one deep-learning framework (TensorFlow or PyTorch)
SQL, including query optimization
Understanding of data warehouses
Basics of model interpretability using SHAP/feature importance, calibration, and bias/fairness
Basic/intermediate knowledge of REST/gRPC APIs, Docker, and Airflow/Kubeflow or equivalent orchestration tools
Advanced English
Basic knowledge of MLOps and model deployment
Experience in startup or newly formed teams
Preferred: Adtech/Martech, CDP/CRM, lookalike/segmentation, recommender systems, or fraud detection experience
Preferred: Spark/Databricks or equivalent big-data tools