Machine Learning Engineer

  • Remote - Argentina

Remote

Software Development

Mid-level

Job description

πŸš€ Join Our Data Products and Machine Learning Development Startup! πŸš€

Mutt Data is a dynamic startup committed to crafting innovative systems using cutting-edge Big Data and Machine Learning technologies.

We are looking for a Machine Learning Engineer who can help us take our team and expertise to the next level. If you’re passionate about constructing systems, presenting innovative solutions, mastering new tools, and architecting robust data architectures, we’d be delighted to connect with you! 🐢

We harness the power of technologies like Spark, Airflow, Kubernetes, MLFlow, Kafka, DBT, Airbyte, DuckDB, Apache Pinot, SQL, and NoSQL Databases, among many others across different cloud providers like Amazon Web Services, Google Cloud Platform, and platforms like Astronomer and DataBricks.

➀ Our Reach: We collaborate with tech startups and major corporations in Argentina, the United States, Brazil, Colombia, Spain, and Uruguay. Our team excels in developing and maintaining large-scale production data systems with exceptional technical expertise. 🌎

➀ Our Partnerships: We’re proud to be associated with organizations like AWS, Astronomer, Google Cloud, Kaszek, H2O.ai Product Minds, and Soda.🀝

🏑Built for a remote life: Mutt Data is remote-first and remote-always. We’ve designed our culture, communications, and tools to support a distributed team since the beginning. Being remote by design allows Mutt Data to be thoughtful and intentional about creating diverse teams and supporting them with a work environment that fits their lives. With a generous PTO policy and Slack channels for every interest, our culture embraces the things happening in your life. Maybe you need to adjust your schedule to care for your family or take a bike ride. At Mutt Data, that’s embraced.

If you have a passion for learning new tools, sharing knowledge with your colleagues, contributing to intricate solutions, fostering open communication, tackling technical challenges head-on, and flourishing in a collaborative, horizontal structure, all while enjoying the benefits of remote work that provide flexibility and the opportunity to cultivate a harmonious work-life balance, this could be the perfect place for you.🌟

These are some of the problems we solve:

➀ Building modern Data Stacks πŸ› οΈ

➀ Real-Time Advertising Auction Systems πŸ“Š

➀ Scalable Cloud Architectures ☁️

➀ Applied Machine Learning to solve business problemsπŸ€–

➀ Promotions optimizationπŸ”

πŸ“š Read about our case studies here

Responsibilities πŸ€“

➀ Lead ML Model Productization: Champion the productization of ML models following MLops best practices, including orchestration, testing, monitoring, and serving, to benefit our clients.

➀ ML POC Development: Collaborate with data scientists to develop meaningful ML Proof of Concepts (POCs) for internal and client requirements.

➀ ML Model Lifecycle Management: Oversee the lifecycle of Machine Learning models, optimizing them when necessary to enhance performance, latency, memory, and throughput.

➀ Business-Technical Translation: Translate business and mathematical/statistical requirements into software implementations, making informed trade-offs between time, quality, and client-specific needs.

➀ Research and Innovation: Explore emerging ML Engineering technologies (Data Science, Data Engineering, DevOps) and techniques to enhance our toolset, best practices, and overall business value.

➀ Bridge DS and DE Roles: Act as a bridge between Data Scientist (DS) and Data Engineer (DE) roles by handling foundational concepts of application development, infrastructure management, data engineering, and data governance.

➀ Project Strategy: Participate in defining project roadmaps, timelines, and estimates for new initiatives.

➀ Knowledge Sharing: Document and disseminate industry-leading practices in AI/ML within the organization.

➀ Technical Interviews: Collaborate on interview processes for technical personnel, including exam reviews and technical interviews.

Required Skills Β πŸ’»

βœ“ Proven Expertise: Demonstrated work experience in roles such as Machine Learning Engineer, ML Architect, Cloud Engineer, or similar.

βœ“ AI/ML Proficiency: In-depth understanding of AI/ML principles, encompassing neural networks, supervised and unsupervised ML models, time series forecasting, and more.

βœ“ Data Architecture Knowledge: Familiarity with Modern Data Architectures, including the implementation of Data Warehouses and Data Lakes, as well as DevOps tool/stack and methodologies (CI/CD, Kubernetes, Docker, gitops, etc.).

βœ“ ETL and ML Workflow Experience: Previous involvement with data processing ETL and ML workflows, e.g., Airflow, MLflow, DBT.

βœ“ Deep Learning Competence: Understanding of Deep Learning frameworks and technologies such as Keras, PyTorch, Tensorflow.

βœ“ Programming Skills: Strong grasp of Python programming language and proficiency in at least one other strongly typed language.

βœ“ Mathematical and Statistical Acumen: Knowledge of mathematical modeling and proficient statistical intuition.

βœ“ MLOps Mastery: Experience in implementing Machine Learning-based systems, including ML model lifecycle management, monitoring, and setting up MLOps pipelines from scratch.

βœ“ Strategic Thinking: Ability to develop implementation plans by weighing the pros and cons of different alternatives.

βœ“ Exceptional capacity for teamwork.

βœ“ English Intermediate Level.

βœ“ Spanish Advanced Level.

Nice to have skills πŸ˜‰

βœ“ Modern Data Stack: Experience with the Modern Data Stack.

βœ“ Cloud-Based AI Services: Hands-on experience with cloud-based AI services like AWS Sagemaker, AWS Textract, GCP Vertex AI, or similar.

βœ“ Software Development Expertise: Profound knowledge of software development methodologies.

βœ“ Problem-Solving Attitude: A positive problem-solving attitude.

βœ“ Consultancy Experience: Previous experience in client-facing tech consultancy roles.

βœ“ Proven Track Record: A track record of delivering high-quality solutions.

βœ“ Cloud Certifications: Certification in cloud platforms, such as AWS Machine Learning.

βœ“ Python Data Libraries: Familiarity with Python Data libraries like SQLAlchemy, Alembic, Great Expectations, etc.

Benefits 😎

πŸ‹οΈβ€β™€οΈ Gympass or Sport Club

🌐 Additional Internet Connectivity Stipend

🎁 Welcome Kit: Mutt provides necessary working equipment if needed, such as a laptop, ergonomic chair, headset, external monitor, and more.

πŸ” Pedidos Ya Pay

πŸŽ‰ Social Paid Events

🏒 Offi Coworking Spaces

πŸ’΅ Salary in USD (Up to 20%)

😎 Mutt Week: Get an additional week of vacation each year.

πŸ“š Paid AWS and GCP Certification Exams

🎈 Birthday Free Day

πŸ—£οΈ In-Company English Lessons

πŸ‘₯ Referral Bonuses

🏑 Remote First Culture

✈️ Annual Mutters’ Trip

Even if your experience only meets some of the bullets on the above lists, we’d love to learn more about you and why you think Mutt Data is the next step in your career. πŸ™ŒπŸ˜Š

Mutt Data is an equal-opportunity employer. We do not discriminate based on gender, religion, race, mental disability, sexual orientation, age, or any other status. All applicants are considered based on their qualifications and merits. At Mutt Data, we inspire an environment of mutual respect and believe diversity and inclusion are crucial to our success.

Are you interested in joining our team? Send us your resume. We can’t wait to meet you! 🀝

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