Machine Learning Engineer
Machine Learning Engineer
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Job Description
Global Data Insight & Analytics organization is looking for a topnotch Software Engineer who has also got Machine Learning knowledge & Experience to add to our team to drive the next generation of AI/ML (Mach1ML) platform. In this role you will work in a small crossfunctional team. The position will collaborate directly and continuously with other engineers business partners product managers and designers from distributed locations and will release early and often. The team you will be working on is focused on building Mach1ML platform an AI/ML enablement platform to democratize Machine Learning across Ford enterprise (like OpenAIs GPT Facebooks FBLearner etc. to deliver nextgen analytics innovation.
We strongly believe that data has the power to help create great products and experiences which delight our customers. We believe that actionable and persistent insights based on high quality data platform help business and engineering make more impactful decisions.
Our ambitions reach well beyond existing solutions and we are in search of innovative individuals to join this Agile team. This is an exciting fastpaced role which requires outstanding technical and organization skills combined with critical thinking problemsolving and agile management tools to support team success.
Responsibilities
What youll be able to do:
As a Software Engineer you will work on developing features for Mach1ML platform support customers in model deployment using Mach1ML platform on GCP and Onprem. You will follow Rally to manage your work. You will incorporate an understanding of product functionality and customer perspective for model deployment. You will work on the cuttingedge technologies such as GCP Kubernetes Docker Seldon Tekton Airflow Rally etc.
Position Responsibilities:
- Work closely with Tech Anchor Product Manager and Product Owner to deliver machine learning use cases using Ford Agile Framework.
- Work with Data Scientists and ML engineers to tackle challenging AI problems.
- Work specifically on the Deploy team to drive model deployment and AI/ML adoption with other internal and external systems.
- Help innovate by researching stateoftheart deployment tools and share knowledge with the team.
- Lead by example in use of Paired Programming for cross training/upskilling problem solving and speed to delivery.
- Leverage latest GCP CICD ML technologies
- Critical Thinking:Able to influence the strategic direction of the company by finding opportunities in large rich data sets and crafting and implementing data driven strategies that fuel growth including cost savings revenue and profit.
- Modelling:Assessments and evaluating impacts of missing/unusable data design and select features develop and implement statistical/predictive models using advanced algorithms on diverse sources of data and testing and validation of models such as forecasting natural language processing pattern recognition machine vision supervised and unsupervised classification decision trees neural networks etc.
- Analytics:Leverage rigorous analytical and statistical techniques to identify trends and relationships between different components of data draw appropriate conclusions and translate analytical findings and recommendations into business strategies or engineering decisions with statistical confidence
- Data Engineering:Experience with crafting ETL processes to source and link data in preparation for Model/Algorithm development. This includes domain expertise of data sets in the environment thirdparty data evaluations data quality
- Visualization:Build visualizations to connect disparate data find patterns and tell engaging stories. This includes both scientific visualization as well as geographic using applications such as Seaborn Qlik Sense/PowerBI/Tableau/Looker Studio etc.
Qualifications
Minimum Requirements we seek:
- Bachelors or masters degree in computer science engineering or related field or a combination of education and equivalent experience.
- 3 years of experience in full stack software development
- 3 years experience in Cloud technologies & services preferably GCP
- 3 years of experience of practicing statistical methods and their accurate application e.g. ANOVA principal component analysis correspondence analysis kmeans clustering factor analysis multivariate analysis Neural Networks causal inference Gaussian regression etc.
- 3 years experience with Python SQL BQ.
- Experience in SonarQube CICD Tekton terraform GCS GCP Looker Google cloud build cloud run Vertex AI Airflow TensorFlow etc.
- Experience in Train Build and Deploy ML DL Models
- Experience in HuggingFace Chainlit Streamlit React
- Ability to understand technical functional nonfunctional security aspects of business requirements and delivering them endtoend.
- Ability to adapt quickly with opensource products & tools to integrate with ML Platforms
- Building and deploying Models (Scikit learn DataRobots TensorFlow PyTorch etc.
- Developing and deploying OnPrem & Cloud environments
- Kubernetes Tekton OpenShift Terraform Vertex AI
Our Preferred Requirements:
- Masters degree in computer science engineering or related field or a combination of education and equivalent experience.
- Demonstrated successful application of analytical methods and machine learning techniques with measurable impact on product/design/business/strategy.
- Proficiency in programming languages such as Python with a strong emphasis on machine learning libraries generative AI frameworks and monitoring tools.
- Utilize tools and technologies such as TensorFlow PyTorch scikitlearn and other machine learning libraries to build and deploy machine learning solutions on cloud platforms.
- Design and implement cloud infrastructure using technologies such as Kubernetes Terraform and Tekton to support scalable and reliable deployment of machine learning models generative AI models and applications.
- Integrate machine learning and generative AI models into production systems on cloud platforms such as Google Cloud Platform (GCP) and ensure scalability performance and proactive monitoring.
- Implement monitoring solutions to track the performance health and security of systems and applications utilizing tools such as Prometheus Grafana and other relevant monitoring tools.
- Conduct code reviews and provide constructive feedback to team members on machine learningrelated projects.
- Knowledge and experience in agentic workflow based application development and DevOps
- Stay up to date with the latest trends and advancements in machine learning and data science.
Employment Type
Full-Time
