Senior Machine Learning Operations Engineer @MMCTech Cluj-Napoca

You will be responsible to build MLOps on cloud – AWS, Databricks;

Build CI/CD pipelines orchestration by Git
Hub Actions
Airflow or similar tools;

You will be responsible to take offline models built by data scientists and turn them into a real machine learning production system;

Setup the deployment process for the ML and gen AI models on AWS Databricks;

Develop and deploy scalable tools and services for our clients to handle machine learning training and inference;

Identify and evaluate new technologies to improve performance, maintainability, and reliability of our clients’ machine learning systems;

You will also be responsible to understand the ML lifecycle and possess the skills to develop pipelines, automate processes, and integrate models into production environments;

Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc. ;

Communicate with clients to build requirements and track progress;

Understand the ML requirements and should also be able to build the MLModels as and when required;

An opportunity to work in a
- growing, innovative company with lots of room for progression and career growth;

A
- friendly environment that encourages learning and initiative;

A yearly budget and the opportunity to build your flexible benefits package (up to 20% of your annual salary);

30+ days off (25 legal days off, 1 extra day off on your birthday, public holiday replacement days, extra buy/sell from your benefits budget);

Performance Bonus scheme

Matching charity contributions, charity days off, and the Pay it Forward charity challenge;

Core benefits - Pension, Life and Medical Insurance, Meal Vouchers, Travel Insurance;

We champion flexible working, and our mission is to help you find YOUR
- life balance, whether that is standard working, flextime working, or working from home.

 Work with our partners to understand business and technology problems or opportunities;

Conceptualize and implement the setup and management of the ML platform built on cloud saas solutions like AWS Sagemaker, Databricks, Snowflake across different regions;

Configure, implement and optimize the ML techstack including AWS databricks including the performance and scalability to create the
-
- class models;

Streamlines ML lifecycle: From data preparation and training to deployment and monitoring;

Works with specialists: Data Engineers, Machine Learning Engineers, Model Deployment Specialists, Monitoring and Observability Engineers, and MLOps Platform Architects;

Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality;

Data science models testing, validation and tests automation;

Collaborate with different stakeholders like MMC infra, MMC security, MMC architecture teams to achieve high availability and scalability over the data platform;

Continuous learning and implementation of latest technologies;

Be innovative in your design thinking and use your expertise to influence the MMC technology roadmap;

Take your architectural designs through our on boarding processes to ensure they meet MMC’s standards and conventions;

Participate in cost estimations during budget cycles;

Empower the development teams to deliver your architectural designs;

Bachelor's or Master's degree in Computer Science, Engineering, or related field;

5 + years good experience in data science and MLOps roles;

Good to have exposure to Big Data / Data Lake frameworks like Spark, Spark Streaming, Python, R, Ni
Fi, AWS S3, Redshift, Glue, Athena etc and tools like Databricks, IDMC ( informatica cloud ), Snowflake;

Excellent verbal and written communication skills in Romanian and English ensuring effective and professional communication with stakeholders;

Experience in using cloud platform – AWS;

Experience with MLOps Frameworks like MLFlow, Airflow etc. , experience with Docker and Kubernetes;

Programming languages like Python and R, good understanding of Linux, knowledge of frameworks such as
- learn, Keras, Py
Torch, Tensorflow, etc. ;

Understanding of microservice based architecture;

Experience of developing and executing ML pipelines on AWS Databricks or Sagemaker;

Understanding of BI Tools like Power
BI, Qlik is an added advantage;

Excellent communication and collaboration skills with the ability to work effectively with
- functional teams;

An inquisitive mind set with a track record of seeking out and implementing new technologies and architectural patterns;

Self-motivated to excel in a remote position, collaborating effectively with a remote team;

You are a
- starter; you can take initiative without waiting for direction;

Ability to take decisions during crisis;

The ability to work in a
- paced environment with changing priorities and deadlines;

You are used to working and communicating with both business and technical stakeholders at varying levels of seniority;

Strong AWS and Databricks experience with ML features;

Experience with developing Gen
AI models;