About Us:

We are a global consultancy committed to helping change makers worldwide shape the future. With a presence in numerous cities across different countries, we work collaboratively with our clients, sharing a common goal of achieving exceptional results, surpassing competition, and redefining industries. Our dedication extends beyond conventional consultancy; we invest in pro bono services, contributing over $1 billion over the next decade to address pressing issues in education, racial equity, social justice, economic development, and the environment. Our commitment to sustainability is evident in our gold rating from EcoVadis, recognizing our efforts in environmental, social, and ethical performance. Since our establishment in 1973, we measure our success by the success of our clients, maintaining the highest level of client advocacy in the industry.

About the Role:

We are seeking an Expert Senior Manager in Machine Learning Engineering to join our dynamic team. As part of our Data Science and Machine Learning Engineering team within the Advanced Analytics Group, you will collaborate with multidisciplinary teams to assess opportunities and devise data-driven solutions for our clients across diverse sectors. You will translate business objectives into actionable data and analytics solutions, leveraging your expertise in machine learning and data engineering. Moreover, you will play a pivotal role in developing innovative analytics solutions and products, transforming prototypes into scalable, production-grade software.

Responsibilities:

• Collaborate closely with business consulting staff and leaders to develop data-driven solutions for clients
• Translate business objectives into data and analytics solutions, deriving actionable insights
• Partner with engineering and product specialists to support the development of innovative analytics solutions
• Develop scalable, production-grade software from existing prototypes
• Manage the development of re-usable frameworks, models, and components
• Drive best practices in machine learning engineering and MLOps
• Cultivate relationships with external data and analytics vendors
• Provide expertise in state-of-the-art machine learning techniques
• Develop, deploy, and support industry-leading machine learning solutions for clients
• Act as a Professional Development Advisor to a team of machine learning engineers
• Support leadership in extending and growing machine learning, engineering, and analytics capabilities
• Contribute to the development of Advanced Analytics intellectual property and identify new opportunities for data science and analytics

Requirements:

• Advanced Degree in a quantitative discipline such as Computer Science, Engineering, Physics, Statistics, or Applied Mathematics
• 10+ years of experience in software engineering, analytics development, or machine learning engineering
• 3+ years of experience in managing data scientists and ML engineers
• Strong understanding of computer science concepts, software design best practices, and the software development lifecycle
• Solid understanding of foundational machine learning concepts and algorithms
• Experience deploying production-grade machine learning solutions on-premise or in the cloud
• Expert knowledge of Python programming and machine learning frameworks (Scikit-learn, TensorFlow, Keras, PyTorch, etc.)
• Experience implementing ML automation, MLOps, and associated tools (e.g., MLflow, Kubeflow)
• Familiarity with DevSecOps principles and industry deployment best practices
• Extensive experience in at least one cloud platform (e.g., AWS, GCP, Azure) and associated machine learning services
• Familiarity with Agile software development practices
• Strong interpersonal and communication skills
• Ability to work independently and collaboratively in a fast-paced environment

Additional Skills:

• Proficiency with core techniques of linear algebra and common optimization algorithms
• Experience using distributed computing engines (e.g., Dask, Ray, Spark)
• Experience with big data technologies and distributed computing engines (e.g., HDFS, Spark, Kafka, Cassandra, Solr, Dask)

Compensation and Benefits:

• Competitive salary commensurate with experience and market rates
• Annual discretionary performance bonus
• Comprehensive benefits package including a 401(k) plan with employer contribution, healthcare, and wellness programs

Note: Salary ranges may vary based on location, experience, and other factors.

[Note: Remove any specific references to the original company name and replace with "our client"]

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