ML Engineer

Coherent Solutions; Athens (GA); Hybride; USD 100 000 - 160 000; Plein temps

Avantages offerts par ce poste

Health insurance

Flexible work options (remote/hybrid)

Training & conferences

Mentorship & career growth

Referral program

Résumé du poste

Coherent Solutions is seeking an early-career ML Engineer to collaborate with senior engineers on internal machine learning initiatives. You will prepare datasets, perform exploratory analyses, and build models for regression, classification, clustering, and anomaly detection.

The role includes feature engineering, experiment tracking, and documentation. You will contribute to reproducible ML pipelines and help deploy models via REST APIs or batch workflows, with a focus on learning and gradual

Qualifications

• 1+ year hands-on Python development with Pandas, NumPy, Scikit-learn, and Jupyter.
• Strong foundation in statistics, probability, and linear algebra; capable of EDA.
• Understanding of supervised/unsupervised learning and common tasks like regression, classification, clustering, dimensionality reduction, and anomaly detection.
• Experience preparing structured datasets with cleaning, transformation, encoding, scaling, and feature engineering.
• Knowledge of train/validation/test splits, cross-validation, data leakage, and model evaluation metrics.
• Familiarity with hyperparameter tuning and reproducible ML pipelines.
• SQL skills for data extraction and analysis.
• Ability to expose models via REST APIs or batch workflows.

Responsabilités

• Prepare and validate structured datasets for ML tasks, including cleaning, transformation, encoding, scaling, and handling missing values.
• Conduct exploratory data analysis to identify patterns and data quality issues.
• Build, test, and compare ML models for regression, classification, clustering, dimensionality reduction, and anomaly detection.
• Develop and select features with guidance from senior engineers.
• Run experiments, tune parameters, and evaluate results with appropriate metrics.
• Maintain reproducible ML pipelines, notebooks, experiments tracking, and documentation.
• Write and maintain automated tests for data and model code.
• Support model deployment through REST APIs or batch processing workflows.
• Document model assumptions, results, limitations, and decisions.
• Collaborate with senior engineers and gradually take ownership of more complex tasks.

Connaissances

Python

Pandas

NumPy

Scikit-learn

Jupyter

Statistics

EDA

English (B2+)

Outils

Docker

Git

pytest

MLflow

FastAPI

Description du poste

Company Background

Coherent Solutions is a global digital product engineering company founded in 1995 and headquartered in Minneapolis, Minnesota. With a presence in nine countries and a team of more than 1,700 engineers, the company provides custom software development and engineering services across web and mobile applications, cloud, DevOps, and data. Coherent Solutions works with clients worldwide to build and scale digital products while fostering a culture of collaboration, transparency, and continuous professional growth.

Project Description

You will work with senior engineers on internal classical machine learning initiatives. The role combines structured learning, practical delivery, and gradual ownership of increasingly complex tasks.

Technologies

• Python, pandas, NumPy, scikit-learn, Jupyter
• SQL
• XGBoost, LightGBM
• MLflow
• FastAPI
• Git, Docker, pytest

What You’ll Do

• Prepare and validate structured datasets for machine learning tasks, including cleaning, transformation, encoding, scaling, and missing-value handling;
• Conduct exploratory data analysis to identify patterns, data quality issues, and opportunities for modeling;
• Build, test, and compare ML models for tasks such as regression, classification, clustering, dimensionality reduction, and anomaly detection;
• Develop and select features with guidance from senior engineers;
• Run experiments, tune model parameters, and evaluate results using appropriate validation approaches and metrics;
• Help maintain reproducible ML pipelines, notebooks, experiment tracking, and technical documentation;
• Write and maintain automated tests for data and model-related code;
• Support the delivery of models through REST APIs or batch-processing workflows;
• Document model assumptions, results, limitations, and technical decisions;
• Work closely with senior engineers, incorporate feedback, and gradually take ownership of more complex tasks;

Job Requirements

• 1+ year of hands-on Python development experience, including experience with pandas, NumPy, scikit-learn, and Jupyter;
• A strong foundation in statistics, probability, and linear algebra, plus exploratory data analysis skills;
• An understanding of supervised and unsupervised learning, and practical experience with regression, classification, clustering, dimensionality reduction, and anomaly detection;
• Experience preparing structured datasets, including cleaning, transformation, encoding, scaling, and missing-value handling, plus practical feature engineering and feature-selection skills;
• An understanding of train/validation/test splits, cross-validation, data leakage, overfitting, and regularization; the ability to select appropriate evaluation metrics, compare models, and perform error analysis;
• Familiarity with hyperparameter tuning and reproducible ML pipelines;
• SQL skills for data extraction and analysis;
• The ability to expose models through REST APIs or batch-processing workflows;
• Familiarity with Git, automated testing, Docker, and basic model monitoring;
• The ability to explain model behavior, assumptions, limitations, and results;
• English at B2 level or higher;

Nice To Have

• XGBoost, time-series analysis, recommendation systems, MLflow, model interpretability, cloud services, production ML monitoring, and GenAI, LLM, RAG, prompt-engineering, or agent-development experience;

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Health insurance;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.