Job Overview

We are expanding our team and are seeking talented individuals for various roles in the Machine Learning domain, including Data Scientists, Data Engineers, ML Engineers, and ML Ops Engineers for all seniority levels (Junior, Mid-Level, Senior, Architect)

Roles

Data Scientist

Key Responsibilities

• Design, develop, and evaluate machine learning models and algorithms.
• Conduct exploratory data analysis and feature engineering.
• Implement state-of-the-art algorithms such as LSTMs, CNNs, Ensemble methods, and Reinforcement Learning.
• Collaborate with cross-functional teams to understand business requirements and translate them into ML solutions.
• Communicate insights and model results to stakeholders through visualizations and reports.

Qualifications

• Proficiency in Python, R, and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Strong statistical analysis and data modeling skills.
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Plotly).
• Knowledge of cloud AI services (e.g., AWS SageMaker, Google AI Platform, Azure ML).

Preferred Qualifications

• Experience with Natural Language Processing (NLP) and Large Language Models (LLMs).
• Familiarity with AI workflows and tools like MLflow, Kubeflow, and DVC.
• Understanding of deep learning architectures and transfer learning.

Data Engineer

Key Responsibilities

• Design and implement robust data pipelines and data warehouses.
• Manage ETL processes to ensure data quality and consistency.
• Work with NoSQL databases (e.g., MongoDB) and big data technologies (e.g., Hadoop, Spark).
• Optimize data workflows for performance and scalability.
• Collaborate with data scientists to provide the necessary data infrastructure.

Qualifications

• Experience with ETL tools and SQL/NoSQL databases.
• Proficiency in programming languages such as Python, Java, or Scala.
• Knowledge of data storage solutions and cloud platforms (e.g., AWS, Azure, Google Cloud).

Preferred Qualifications

• Familiarity with data versioning tools like Delta Lake or LakeFS.
• Experience with streaming data frameworks (e.g., Kafka, Flink).
• Understanding of data governance and security best practices.

Machine Learning Engineer

Key Responsibilities

• Implement and deploy machine learning models in production environments.
• Design and build scalable ML systems and pipelines.
• Optimize model performance and deployment processes.
• Collaborate with data scientists and engineers on integrated projects.
• Monitor and maintain ML systems to ensure reliability and efficiency.

Qualifications

• Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch).
• Experience with model deployment tools (e.g., Docker, Kubernetes).
• Strong software engineering skills in languages like Python or Go.

Preferred Qualifications:

• Knowledge of MLOps technologies and CI/CD pipelines (e.g., Jenkins, GitLab CI).
• Experience with cloud AI services and infrastructure (e.g., AWS SageMaker, Google AI Platform).
• Familiarity with co-pilots and automated ML tools.

ML Ops Engineer

Key Responsibilities

• Design and implement ML infrastructure and CI/CD pipelines.
• Ensure reliable model deployment and monitoring practices.
• Manage and optimize ML model lifecycle from development to production.
• Collaborate with ML engineers and data scientists to streamline operations.
• Implement best practices for model lifecycle management and versioning.

Qualifications

• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud).
• Proficiency with CI/CD tools and practices (e.g., Jenkins, GitLab CI).
• Familiarity with monitoring and logging tools (e.g., Prometheus, Grafana).

Preferred Qualifications

• Knowledge of MLOps frameworks like MLflow, Kubeflow, or TFX.
• Experience with automated model retraining and deployment.
• Understanding of AI workflows and lifecycle management.

Benefits

• Fully remote work environment.
• Competitive salary.
• Professional development opportunities and support for certifications.
• Collaborative and inclusive company culture.
• Cutting-edge technology and resources to support your work.
• Opportunity to work with a talented and passionate team driving innovation in AI.
• Flexibility to facilitate the participation in Tech Conferences
• Ability to work on your own suggested projects during working hours having IP shares

What you should know?

We are new company. Which means we run at a very high tempo. We work hard.

How to Apply?

To apply, please submit your resume in pdf format and a cover letter in the following form detailing your relevant experience and why you are a great fit for this role. We look forward to hearing from you!

About Us

kAInematics is an innovative AI company at the forefront of artificial intelligence and machine learning technologies. Our mission is to revolutionize industries with cutting-edge AI solutions that drive efficiency, enhance decision-making, and deliver tangible results. We are a dynamic and forward-thinking team dedicated to fostering a collaborative and inclusive work environment.