Machine Learning Engineer
Date: Sep 30, 2024
Location: Dhaka, BD, 1212 BD
Company: Optimizely
At Optimizely, we're on a mission to help people unlock their digital potential. We do that by reinventing how marketing and product teams work to create and optimize digital experiences across all channels. With Optimizely One, our industry-first operating system for marketers, we offer teams flexibility and choice to build their stack their way with our fully SaaS, fully decoupled, and highly composable solution.
We are proud to help more than 10,000 businesses, including H&M, PayPal, Zoom, and Toyota, enrich their customer lifetime value, increase revenue and grow their brands. Our innovation and excellence have earned us numerous recognitions as a leader by industry analysts such as Gartner, Forrester, and IDC, reinforcing our role as a trailblazer in MarTech.
At our core, we believe work is about more than just numbers -- it's about the people. Our culture is dynamic and constantly evolving, shaped by every employee, their actions and their stories. With over 1500 Optimizers spread across 12 global locations, our diverse team embodies the "One Optimizely" spirit, emphasizing collaboration and continuous improvement, while fostering a culture where every voice is heard and valued.
Introduction
We are looking for a machine learning engineer who’s passionate about building scalable machine learning applications and using data-driven approaches to generate business insights. As a key member of the ML Engineering, Data Services team, you will have the opportunity to build machine learning models and design/automate/deploy machine learning pipelines to solve key business problems across an array of technologies. You will be working with a group of ML engineers, data engineers, and analysts to build intelligent & innovative solutions for Optimizely’s internal teams. You will be highly encouraged to explore new technologies, and data sources and come up with innovative solutions that could take the team’s data science machine learning engineering capability to the next level.
Job Responsibilities
- Leverage cutting-edge AI/ML methods to develop AI/ML-powered solutions that align with business objectives.
- Prepare dataset/data-pipeline to feed into the machine learning models.
- Optimize ML applications to improve performance, speed, and scalability
- Work with internal stakeholders, analysts, engineers to explore and understand business data.
- Conduct experiments and test different technical approaches
- Collaborate with the data engineering team to ensure clean records
- Implement machine learning model lifecycle management framework.
- Build/maintain model performance tracking tools, to monitor model performance, identify drivers and provide recommendations for optimization
- Author technical documentation and reports to communicate process and results
Knowledge and Experience
Minimum qualifications:
- 1 to 4 years of hands-on experience in machine learning models, applications, and pipelines.
- Experience in developing, testing, debugging, maintaining, or launching ML products, as well as software design and architecture.
- Proficiency in one or more programming languages (preferably Python).
- Working knowledge of one or more SQL languages (preferably Snowflake, PostgreSQL, MySQL).
- Knowledge of common machine learning and statistical packages, frameworks, and concepts.
- Experience/knowledge of working with large data sets, distributed computing, and cloud computing platforms.
- Experience using CI/CD tools and version control systems (e.g., Git).
- Excellent written and verbal communication skills in English.
Preferred qualifications:
- Strong understanding of machine learning algorithms and their practical implementation.
- Excellent problem-solving skills and the ability to translate business requirements into technical solutions.
- Experience deploying machine learning models in production environments.
- Excellent analytical and problem-solving skills with keen attention to detail.
- A team-oriented mindset, believing that AI/ML is a collaborative effort.
Education
Bachelor’s degree in Computer Science, Mathematics, Statistics, Physics, or a related field with project experience in machine learning and statistical modeling.
Competencies
Our culture is the most important thing we offer. We continuously aim to provide a high-growth space, both virtually and in person, where you can do your best work and, in the process, unlock your boundless potential. Our new, cutting-edge office space in Dhaka is a testament to our dedication to enhancing your work experience. This state-of-the-art workspace features open workstations, a fully equipped kitchen, a nap room for relaxation, a tranquil zen garden, and an entertaining area, all designed to provide you with the ideal environment to thrive and grow.
As part of our commitment to you, here are other benefits and perks you can expect:
- Best-in-class compensation plans
- Two annual festival bonuses
- Recognition and rewards programs
- Paid Maternity (4 months) & Paternity Leave (12 weeks)
- Flexible vacations days and working hours
- Annual Work/Service Anniversary Leave
- Comprehensive medical & life insurance for you and your dependants
- Volunteering opportunities to make a difference
- Chance to work alongside our incredible global team
- Monthly and quarterly regional and global team-building events
- Communal transport facilities inside Dhaka to and from the office
- Free catered lunch every day
- An agile performance review process that encourages ongoing transparency between managers and direct reports
- Enablement program and soft skill training to support internal career growth and development
At Optimizely, our standardized language is English, and it is crucial to have good English communication skills to be successful in your global role. All our external and cross-location communication is done in US English (en-us), but internally you can speak in whichever native language you most identify with.
Optimizely is committed to a diverse and inclusive workplace. Optimizely is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.