Senior Specialist, ML Ops Engineering

Job Description

Machine Learning Engineer (MLOps) Technical Lead, Data Science and Scientific Informatics

The Data Science and Scientific Informatics Team at Research and Development Sciences IT (RaDS-IT) of our company is seeking a Lead Machine Learning Engineer for MLOps. The successful candidate will engage in exploration, design, and implementation of features to support new MLOps use cases for a growing and diverse range of models and platforms. This role will involve the deployment and operationalization of machine learning models across multiple domains, ensuring that our analytics capabilities are robust and scalable.

Responsibilities:

• Serve as MLOps representative to stakeholders and lead discussions with them.

• Participate in MLOps technical strategy discussions and lead implementation.

• Execute on MLOps strategy and architectural decisions.

• Make key technical decisions independently.

• Lead other technical team members and oversee development work.

• Collaborate with data scientists, software engineers, and product teams to design, implement, and maintain production-level machine learning pipelines and workflows.

• Develop and automate processes for data preprocessing, feature engineering, model training, and evaluation to enhance the reliability and scalability of machine learning applications.

• Utilize MLOps principles to streamline the model deployment process, ensuring models are easily retrainable and maintainable as new data becomes available.

• Monitor and evaluate model performance in a production environment, while ensuring compliance with industry standards and best practices.

• Prepare and present findings and developments to internal stakeholders, contributing to strategic decision-making and operational improvements in MLOps.

• Stay current with industry trends and best practices in machine learning, data engineering, and MLOps, and actively contribute to the innovation of methodologies within the team.

Required Experience and Skills:

• Bachelor's degree in computer science, Data Science, Applied Mathematics, or a related Science and Engineering fields.

• A minimum of three years' experience in ML Ops

• Previous MLOps experience from deploying models to model maintenance and management.

• Knowledge of machine learning algorithms and data science techniques.

• Proficiency in Python (including a familiarity with libraries and frameworks for machine learning (e.g., scikit-learn, TensorFlow, PyTorch).

• Experience with MLOps tools and platforms (e.g., MLFlow, Docker, SageMaker or other cloud-based solutions).

• Familiarity with version control systems (e.g., Git), GitHub actions and CI/CD processes to manage model lifecycle.

• Experience with Apache Airflow or similar orchestration tools.

• Knowledge of big data technologies and cloud computing environments (AWS, Databricks, EC2).

• Excellent analytical and problem-solving capabilities with a keen interest in applying creative solutions to strategic initiatives.

• Strong organizational skills with the ability to manage multiple tasks and meet deadlines in a fast-paced environment.

• Effective verbal and written communication skills for conveying complex information to colleagues and stakeholders.

Preferred Experience and Skills (not all required):

• A Master's degree is a plus.

• Experience with Domino, Dataiku

• Deploying LLMs and Foundation models.

• Building APIs (FastAPI, Flask)

• Grafana Dashboards

• Building python packages, Artifactory

• Experience with R, Julia

Current Employees apply HERE

Current Contingent Workers apply HERE

US and Puerto Rico Residents Only:

Our company is committed to inclusion, ensuring that candidates can engage in a hiring process that exhibits their true capabilities. Please click here if you need an accommodation during the application or hiring process.

As an Equal Employment Opportunity Employer, we provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other applicable legally protected characteristics. As a federal contractor, we comply with all affirmative action requirements for protected veterans and individuals with disabilities. For more information about personal rights under the U.S. Equal Opportunity Employment laws, visit:

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We are proud to be a company that embraces the value of bringing together, talented, and committed people with diverse experiences, perspectives, skills and backgrounds. The fastest way to breakthrough innovation is when people with diverse ideas, broad experiences, backgrounds, and skills come together in an inclusive environment. We encourage our colleagues to respectfully challenge one another’s thinking and approach problems collectively.

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U.S. Hybrid Work Model

Effective September 5, 2023, employees in office-based positions in the U.S. will be working a Hybrid work consisting of three total days on-site per week, Monday - Thursday, although the specific days may vary by site or organization, with Friday designated as a remote-working day, unless business critical tasks require an on-site presence.This Hybrid work model does not apply to, and daily in-person attendance is required for, field-based positions; facility-based, manufacturing-based, or research-based positions where the work to be performed is located at a Company site; positions covered by a collective-bargaining agreement (unless the agreement provides for hybrid work); or any other position for which the Company has determined the job requirements cannot be reasonably met working remotely. Please note, this Hybrid work model guidance also does not apply to roles that have been designated as “remote”.

The salary range for this role is

This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee’s position within the salary range will be based on several factors including, but not limited to relevant education, qualifications, certifications, experience, skills, geographic location, government requirements, and business or organizational needs.

The successful candidate will be eligible for annual bonus and long-term incentive, if applicable.

We offer a comprehensive package of benefits. Available benefits include medical, dental, vision healthcare and other insurance benefits (for employee and family), retirement benefits, including 401(k), paid holidays, vacation, and compassionate and sick days. More information about benefits is available at https://jobs.merck.com/us/en/compensation-and-benefits.

You can apply for this role through https://jobs.merck.com/us/en (or via the Workday Jobs Hub if you are a current employee). The application deadline for this position is stated on this posting.

San Francisco Residents Only: We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance

Los Angeles Residents Only: We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance

Search Firm Representatives Please Read Carefully
Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.

Employee Status:

Regular

Relocation: