Senior AI/ML Engineer

Fincons Group

. Develop and deploy AI/ML solutions, including machine learning models, Generative AI, LLMs, NLP systems, APIs, and RAG architectures .

Posted 11/6/2026full-timeRemote • ItalySeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying AI/ML solutions, managing the full ML lifecycle, and ensuring compliance with data governance and AI Act requirements. Proficient in programming languages and frameworks essential for AI development, with strong analytical skills for handling large datasets.

Highest-signal resume keywords

Machine Learning Lifecycle ManagementAI/ML Solution DevelopmentData Governance and ComplianceProficiency in Python and SQLExpertise in Generative AI and NLP

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningArtificial IntelligenceData ManagementStatistical AnalysisDeep LearningGenerative AINatural Language ProcessingData CleaningModel TrainingFeature Engineering

Soft Skills

Excellent Communication SkillsInterpersonal SkillsTeam CollaborationResults-Oriented MindsetAutonomous Work Ability

Tools & Technologies

PythonRSQLTensorFlowPyTorchScikit-learnPandasFastAPIMLflowKubeflow

Certifications & Qualifications

Certificate in PythonCertificate in PandasCertificate in SQLCertificate in Deep LearningCertificate in Time SeriesCertificate in Data CleaningCertificate in Machine Learning Explainability

Industry Keywords

AI Act ComplianceData QualityBias Detection and MitigationMLOpsAgile Software DevelopmentData VisualizationMachine Translation Quality EvaluationAnomaly DetectionStatistical TestingLifecycle Management

Tech Stack

Tools & technologies

CloudOpenShiftPandasPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Develop and deploy AI/ML solutions, including machine learning models, Generative AI, LLMs, NLP systems, APIs, and RAG architectures
Manage the full ML lifecycle, from data preparation and feature engineering through model training, deployment, monitoring, retraining, and MLOps automation
Ensure data quality, governance, compliance, bias detection and mitigation, data integrity, AI Act compliance, and responsible AI practices
Design and optimize AI architectures using programming languages, ML frameworks, libraries, and cloud-based AI platforms
Analyze large and complex datasets using SQL, data lakes, visualization tools, anomaly detection systems, and statistical methods
Collaborate with business and technical stakeholders to define requirements, data rules, technical standards, and solution roadmaps
Produce technical documentation and presentations for technical and non-technical audiences
Stay current with AI research and innovation by evaluating and piloting new technologies

Requirements

What you’ll need

Master degree
At least 15 years of experience in Machine Learning / Artificial Intelligence / data management
Ability to participate in multilingual meetings
Ability to understand, speak and write English
Very good knowledge of English, spoken and written, corresponding to Level C1
Excellent interpersonal and communication skills
Ability to work in a team as well as autonomously
Results-oriented mindset, focused on delivering
Good applied statistics skills, including distributions, statistical testing, and regression
Proficiency with programming languages and key libraries essential for AI development
Data-driven mindset
Certificate of course attendance on Python, Pandas, SQL
Certificate of course attendance on Deep Learning
Certificate of course attendance on Time Series
Certificate of course attendance on Data cleaning
Certificate of course attendance on Machine Learning Explainability
Strong proficiency in Python, R, SQL, TensorFlow, PyTorch, scikit-learn, pandas, and FastAPI
Expertise in ML algorithms, Deep Learning, Generative AI, LLMs, NLP, classification models, and model alignment techniques
Strong knowledge of data governance, data quality, data cleaning, lifecycle management, and analytics on large-scale structured and unstructured datasets
Experience with LangChain, LlamaIndex, Semantic Kernel, MLflow, Kubeflow, OpenShift, cloud-based AI solutions, and end-to-end MLOps practices
Knowledge of AI security, AI Act requirements, bias detection and mitigation, explainability using SHAP, and AI risk management
Experience in machine translation quality evaluation, information extraction, data visualization, and agile software development methodologies

Benefits

Comp & perks

No specific benefits or compensation extras stated