Offer summary

Qualifications:

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field., 5-7 years of experience as a full-stack developer with hands-on experience in front-end and back-end development., 3+ years of experience implementing and deploying machine learning models into production environments., Strong proficiency in front-end technologies (HTML, CSS, JavaScript, React.js, Angular, or Vue.js) and back-end technologies (Node.js, Python, Java)..

Key responsabilities:

Design, develop, and maintain scalable front-end and back-end applications.

Collaborate with data scientists to integrate and deploy machine learning models into production systems.

Architect end-to-end systems for seamless integration of ML models, ensuring scalability and high availability.

Mentor junior developers and collaborate with cross-functional teams to implement data-driven solutions.

Job description

PharmaForceIQ is a US-based cutting-edge life sciences omnichannel marketing and analytics SaaS platform company that partners with pharmaceutical, biotech and other life sciences companies to help deliver the Right Message to the Right Physician through the Right Channel at the Right Time by deploying the power of advanced predictive analytics and machine learning. The company’s focus on the life sciences industry has generated deep expertise in the nuances and complexities involved in the use of life sciences data to make drug marketing more effective.

The Role

Responsibilities

Full Stack Development:
Design, develop, and maintain both front-end and back-end applications that are scalable and efficient.
Build responsive, user-friendly interfaces using modern front-end technologies (React, Angular, or Vue.js).
Develop RESTful APIs and integrate them seamlessly with the front-end.
Implement and optimize back-end services using technologies such as Node.js, Python, or Java.
Work with relational and NoSQL databases (e.g., MariaDB,MySQL, MongoDB, PostgreSQL) to store and manage data.
Machine Learning Integration:
Collaborate with data scientists to integrate ML models into production systems.
Work on deploying ML models in real-time environments for features like recommendation systems, predictive analytics, and data insights.
Develop, fine-tune, and optimize ML algorithms and models to improve the application's performance.
Build automated data pipelines for model training, evaluation, and prediction.
Architecture & System Design:
Architect end-to-end systems for seamless integration of ML models into applications, ensuring scalability and high availability.
Design and implement scalable data storage solutions to support ML workflows (batch and real-time).
Optimize both the front-end and back-end performance for latency-sensitive ML tasks.
Collaboration & Leadership:
Work closely with product managers to understand user needs and design new features.
Mentor junior developers, provide code reviews, and promote best practices in software development and machine learning.
Collaborate with cross-functional teams, including data scientists, engineers, and business analysts, to implement data-driven solutions.
Testing & Debugging:
Write comprehensive unit tests and integration tests for both the application code and ML models.
Identify bottlenecks and troubleshoot issues related to the front-end, back-end, and machine learning models.
Continuously improve the codebase through refactoring and performance optimization.
Continuous Learning & Improvement:
Stay updated with the latest advancements in machine learning techniques, full-stack development trends, and software engineering best practices.
Research and evaluate new tools, technologies, and frameworks that could improve development processes and application performance.

Ideal Profile

Education: Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field (or equivalent practical experience).
Experience:
5-7 years of experience as a full-stack developer, with significant hands-on experience in both front-end and back-end development.
3+ years of experience implementing and deploying machine learning models into production environments.
Strong proficiency in front-end technologies (HTML, CSS, JavaScript, React.js, Angular, or Vue.js).
Experience with back-end technologies such as Node.js, Python (Django, Flask),FastAPI, Java,
Experience with databases: SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis).
Familiarity with ML libraries and frameworks ( Scikit-learn, Keras).
Solid understanding of data processing frameworks (Pandas, NumPy) and visualization tools (Matplotlib, Seaborn).

Preferred

Experience deploying machine learning models using cloud platforms (AWS, Databricks)
Databricks experience a HUGE plus.
Familiarity with containerization (Docker) and orchestration (Kubernetes).
Knowledge of CI/CD pipelines and DevOps practices.
Familiarity with Agile methodologies and project management tools like Jira, Trello, or Asana.

Skills

Programming Languages: JavaScript, ReactJS, Python, TypeScript, SQL, etc.
Machine Learning: Model training, tuning, deployment, and scaling.
DevOps & Cloud Platforms: AWS, Docker, Kubernetes.
Version Control: Git/GitHub/GitLab.
Soft Skills:
Excellent problem-solving and debugging skills.
Strong communication and collaboration skills to work in cross-functional teams.
Ability to prioritize tasks and meet deadlines in a fast-paced environment.

What's on Offer?