Machine Learning Engineer

Posted 5 months agoViewed

💎 Seniority level: Senior, At least 2 years

📍 Location: Italy

🔍 Industry: AI solutions for regulated industries

🏢 Company: iGenius👥 101-250💰 $20,161,290 Series A almost 3 years agoArtificial Intelligence (AI)Business Intelligence Analytics Information Technology

🗣️ Languages: English

⏳ Experience: At least 2 years

🪄 Skills: DockerPythonSQLGitMachine LearningNumpyPyTorchPandasTensorflow

Requirements:

A Master’s Degree or PhD in quantitative fields, like Computer Science, Engineering, Stats, Math, or Physics.
At least 2 years of proven experience as a Machine Learning Engineer (or a PhD).
Understanding of the fundamentals of statistics and machine learning.
Knowledge in at least one applied machine learning field.
Superb Python programming skills and experience with data science libraries.
Experience with deep learning models using TensorFlow or PyTorch.
Knowledge of version control systems and container tools.

Responsibilities:

Work side-by-side with Developers, Designers, and Data Scientists to understand customers’ needs.
Propose insightful solutions and implement/test machine learning models as efficient services integrated into the product ecosystem.
Explore state-of-the-art Machine Learning research to improve current products and develop new ones.
Continuously improve your scientific and engineering skills while mentoring others.

Apply

Related Jobs

Apply

🔥 Machine Learning Engineer (Staff / Sr Staff)

Posted about 2 months ago

📍 United States, Canada, Europe

🧭 Full-Time

🔍 Software Development

🏢 Company: Equilibrium Energy👥 101-250💰 $33,000,000 Series A almost 2 years agoPower Grid Energy Commercial

🔧 Requirements

Proficiency and 5+ years experience in Python software development
Familiarity with automated build, deployment, and orchestration tools such as CI/CD, Pants, Docker, Metaflow, and Kubernetes
Strong understanding of data pipelines, ETL, and data infrastructure
Experience with observability tooling like Grafana, Honeycomb, and Prometheus
Experience with common machine learning algorithms and libraries (xgboost, sklearn, pytorch, pandas, polars, pandera)
Prior experience in operationalizing machine learning workflows
Agility in working with cross-functional teams and adapting to new work methodologies
Familiarity with agile practices, or a willingness to learn
Strong communication skills for collaborating within a remote-first team that works internationally across timezones

💡 Responsibilities

Develop and maintain scalable ML pipelines, used to support forecasting and optimization models
Design frameworks that support model experimentation, hyperparameter tuning, training, and deployment
Collaborate closely with data scientists to understand new model requirements and together implement solutions that are robust, validated, and scalable
Integrate with data and compute infrastructure to optimize resource utilization and performance
Implement automated testing and monitoring for ML models in production
Partner with our Product and Customer Delivery teams to enable external customers to perform similar tasks to our internal scientists, with minimal code divergence and following security best practices
Stay up-to-date with the latest advancements in ML engineering and integrate best practices into the platform

AWSDockerPythonAgileETLKubernetesMachine LearningPyTorchData scienceGrafanaPrometheusPandasCommunication SkillsCI/CD

Posted about 2 months ago

Apply

🔥 Machine Learning Engineer (AI/ML)

Posted about 2 months ago

📍 North America, Western EU

🧭 Full-Time

🔍 Software Development

🏢 Company: Intangible👥 11-50💰 $4,000,000 Seed 3 months agoDigital Marketing SaaS Marketing Software

🔧 Requirements

Strong experience with modern NLP/LLM frameworks (e.g., Transformers, LangChain).
Experience with data storage and retrieval with vector databases.
Experience with graph databases (e.g., Neo4j, RDF, property graphs).
Proficient in Python and ML libraries (e.g., PyTorch, TensorFlow).
Ability to ship features end-to-end.

💡 Responsibilities

Build NLP pipelines that extract intent, entities, and semantic structure from user input.
Analyze opportunities for improving the AI system's performance and personalization.
Integrate cloud and client LLMs to drive creative workflows.
Design and maintain knowledge graphs to represent world, character, and story data.
Prototype and apply AI features in collaboration with product and engineering teams.
Fine-tune or augment foundation models for domain-specific tasks.

AWSDockerPythonSoftware DevelopmentCloud ComputingKubernetesMachine LearningPyTorchAlgorithmsData StructuresREST APITensorflowData modeling

Posted about 2 months ago

Apply

🔥 Senior Machine Learning Engineer - Fraud

Posted 3 months ago

📍 Africa, Europe, or the Americas

🧭 Full-Time

🔍 Software Development

🏢 Company: Zepz👥 1001-5000💰 $267,000,000 Series F 8 months ago🫂 Last layoff over 1 year agoMobile Payments Financial Services Payments FinTech

🔧 Requirements

4+ years of professional experience training and deploying models that deliver measurable value (regression, clustering, decision trees, cost-sensitive Machine Learning etc with an emphasis on gradient boosting-based methods).
You have strong SQL skills, confidently able to pull and manipulate data to get into the desired format for modelling (CTEs, joins, case statements, subqueries)
Possess strong Python skills, able to automate processes and deploy applications. you are able to deploy your stuff and be able to set up at least basic monitoring.
Familiar with building and deploying web applications using Python web frameworks.

💡 Responsibilities

Modernization our FinCrime Machine Learning Pipeline
Evaluate and integrate new data sources for our algorithms, aligning with Data Engineering and Analytical Engineers' best practices for dbt
In collaboration with Data Scientist, automate the training and deployment of updated models, ensuring the output is tested, scalable and documented and checks are in place to identify drift.
Help build experiments framework to evaluate new models, third-party data sources and tooling.
Translate commercial requirements into technical solutions, converting real-world problems into solvable data science projects, resulting in insights that further the strategy and enable visibility into key results
Improving existing models through greater scrutiny of the methodology and improving the input data
Develop strategies and tools to help less technical individuals understand and use the models and results.

AWSDockerPythonSQLKubernetesMachine LearningNumpyAlgorithmsData scienceData StructuresRegression testingPandasCommunication SkillsAnalytical SkillsCI/CDProblem SolvingRESTful APIsDevOpsData visualizationData modeling

Posted 3 months ago

Apply

🔥 Senior Machine Learning Engineer (Europe)

Posted 7 months ago

📍 Europe

🧭 Full-Time

💸 103000 - 156000 USD per year

🔍 Commercial insurance

🏢 Company: Kalepa👥 11-50💰 $14,000,000 Series A over 3 years agoArtificial Intelligence (AI)Big Data Technical Support InsurTech Insurance Commercial Insurance Software

🔧 Requirements

5+ years of experience in engineering and data science.
In-depth understanding of applied machine learning algorithms, especially NLP and statistics.
Experience with Python and major data science libraries.
Comfort with data science and engineering required to bring models to production.
Interest in using a variety of technologies for problem-solving.

💡 Responsibilities

Lead the framing, development, and deployment at scale of machine learning models.
Turn vast amounts of structured and unstructured data into insights about behavior and risk.
Work closely with Product Management and Software Engineers.

PythonMachine LearningAlgorithmsData science

Posted 7 months ago

Apply